Giselle Thibaudeau

Effects of lithium on pigmentation in the embryonic zebrafish (Brachydanio rerio).

Pigment cell precursors of the embryonic zebrafish give rise to melanophores, xanthophores and/or iridophores. Cell signaling mechanisms related to the development of pigmentation remain obscure. In order to examine the mechanisms involved in pigment cell signaling, we treated zebrafish embryos with various activators and inhibitors of signaling pathways. Among those chemicals tested, LiCl and LiCl/forskolin had a stimulatory effect on pigmentation, most notable in the melanophore population. We propose that the inositol phosphate (IP) pathway, is involved in pigment pattern formation in zebrafish through its involvement in the: (1) differentiation/proliferation of melanophores; (2) dispersion of melanosomes; and/or (3) synthesis/deposition of melanin. To discern at what level pigmentation was being effected we: (1) counted the number of melanophores in control and experimental animals 5 days after treatment; (2) measured tyrosinase activity and melanin content; and (3) employed immunoblotting techniques with anti-tyrosine-related protein-2 and anti-melanocyte-specific gene-1 as melanophore-specific markers. Although gross pigmentation increased dramatically in LiCl- and LiCl/forskolin treated embryos, the effect on pigmentation was not due to an increase in the proliferation of melanophores, but was possibly through an increase in melanin synthesis and/or deposition. Collectively, results from these studies suggest the involvement of an IP-signaling pathway in the stimulation of pigmentation in embryonic zebrafish through the synthesis/deposition of melanin within the neural crest-derived melanophores.

Molecular morphology and function of bull spermatozoa linked to histones and associated with fertility

Sub-par fertility in bulls is influenced by alterations in sperm chromatin, and it might not be solved with increased sperm concentration in artificial insemination. Appropriate histone retention during sperm chromatin condensation plays critical roles in male fertility. The objective of this study was to determine failures of sperm chromatin condensation associated with abnormal persistence or accessibility of histones by aniline blue (ANBL) test, expression levels, and cellular localizations of one variant and two core histones (H3.3, H2B, and H4 respectively) in the spermatozoa of low-fertility (LF) vs high-fertility (HF) bulls. The expression levels and cellular localizations of histones in spermatozoa were studied using immunoblotting, immunocytochemistry, and staining methods. The bioinformatics focused on the sequence identity and evolutionary distance of these proteins among three mammalian species: bovine, mouse, and human. We demonstrated that ANBL staining was different within the LF (1.73 (0.55, 0.19)) and HF (0.67 (0.17, 0.06)) groups (P<0.0001), which was also negatively correlated with in vivo bull fertility (r=-0.90, P<0.0001). Although these histones were consistently detectable and specifically localized in bull sperm cells, they were not different between the two groups. Except H2B variants, H3.3 and H4 showed 100% identity and were evolutionarily conserved in bulls, mice and humans. The H2B variants were more conserved between bulls and humans, than in mice. In conclusion, we showed that H2B, H3.3, and H4 were detectable in bull spermatozoa and that sperm chromatin condensation status, changed by histone retention, is related to bull fertility.

Coloration of Anuran Tadpoles (Amphibia): Development, Dynamics, Function, and Hypotheses

Colorations of anuran tadpoles surely function in many of the same ways that have been ascribed to color and pattern in other animals, but the paucity of data forces one to look to other groups to generate hypotheses. Such an action often occurs because of the difficulty of defining specific fitness parameters to larval forms. The commonly muted colorations of tadpoles are typically considered to function only in some form of crypsis, but we discuss other functions in the particular context of behavioral ecology and changes induced by various kinds of coinhabitants. We review the development, terminology, diversity, and functions of coloration in tadpoles and then pose various questions for future research. We strongly support a broad-based perspective that calls for an integration of several fields of research.

A novel sample preparation method that enables nucleic acid analysis from ultrathin sections.

The ability to isolate and perform nucleic acid analyses of individual cells is critical to studying the development of various cell types and structures. We present a novel biological sample preparation method developed for laser capture microdissection-assisted nucleic acid analysis of ultrathin cell/tissue sections. We used cells of the mitotic bed of the tadpole teeth of Lithobates sphenocephalus (Southern Leopard Frog). Cells from the mitotic beds at the base of the developing teeth series were isolated and embedded in the methacrylate resin, Technovit® 9100®. Intact cells of the mitotic beds were thin sectioned and examined by bright-field and transmission electron microscopy. The cytological and ultrastructural anatomy of the immature and progressively more mature tooth primordia appeared well preserved and intact. A developmental series of tooth primordia were isolated by laser capture microdissection (LCM). Processing of these cells for RNA showed that intact RNA could be isolated. The study demonstrates that Technovit® 9100® can be used as an embedding medium for extremely small tissues and from individual cells, a prerequisite step to LCM and nucleic acid analyses. A relatively small amount of sample material was needed for the analysis, which makes this technique ideal for cell-specific analyses when the desired cells are limited in quantity.

Laser microdissection of semi-thin sections from plastic-embedded tissue for studying plant–organism developmental processes at single-cell resolution

The ability to analyze the gene activity occurring within a single cell has ushered in a new understanding of complex biological processes. Furthermore, this capability has established the prerequisite technologies for the analysis of cells involved in complex pathogenic and/or symbiotic interactions. Collectively, the identification of biological models permitting the analysis of individual cells and improvements in histological technology are allowing for analyses of cells positioned within tissues and involved in complex cellular interactions at unprecedented resolution. Here, a plastic embedding procedure is used for laser microdissection of plant tissues infected with a pathogen. This technique enabled the acquisition of nucleic acids from semi-thin sections that can be used for downstream biological studies of host–pathogen interaction at the single-cell resolution.

Size and medium conductivity dependence on dielectrophoretic behaviors of gas core poly-l-lysine shell nanoparticles

Dynamic (dis)assembly of biocompatible nanoparticles into 3D, packed structures would benefit drug delivery, films, and diagnostics. Dielectrophoretic (DEP) microdevices can rapidly assemble and manipulate polarizable particles within nonuniform electric fields. DEP has primarily discerned micrometer particles since nanoparticles experience smaller forces. This work examines conductivity and size DEP dependencies of previously unexplored spherical core‐shell nanoparticle (CSnp) into 3D particle assemblies. Poly‐l‐lysine shell material was custom synthesized around a gas core to form CSnps. DEP frequencies from 1 kHz to 80 MHz at fixed 5 volts peak‐to‐peak and medium conductivities of 10−5 and 10−3 S/m were tested. DEP responses of ∼220 and ∼400 nm poly‐l‐lysine CSnps were quantified via video intensity densitometry at the microdevices quadrapole electrode center for negative DEP (nDEP) and adjacent to electrodes for positive DEP. Intensity densitometry was then translated into a relative DEP response curve. An unusual nDEP peak occurred at ∼57 MHz with 25–80 times greater apparent nDEP force. All electrical circuit components were then impedance matched, which changed the observed response to weak positive DEP at low frequencies and consistently weak nDEP from ∼100 kHz to 80 MHz. This impedance‐matched behavior agrees with conventional Clausius–Mossotti DEP signatures taking into account the gas cores contributions to the polarization mechanisms. This work describes a potential pitfall when conducting DEP at higher frequencies in microdevices and concurrently demonstrates nDEP behavior for a chemically and structurally distinct particle system. This work provides insight into organic shell material properties in nanostructures and strategies to facilitate dynamic nanoparticle assemblies.

Involvement of a LiCl-Induced Phosphoprotein in Pigmentation of the Embryonic Zebrafish (Dania rerio)

The embryonic zebrafish (Danio rerio) is rapidly becoming an important model organism for studies of early events in vertebrate development. Neural crest-derived pigment cell precursors of the embryonic zebrafish give rise to melanophores, xanthophores, and/or iridophores. Cell-signaling mechanisms related to the development of pigmentation and pigment pattern formation remain obscure. In this study, zebrafish embryos were treated with various signaling-related molecules - LiCl (an inositol-phosphatase inhibitor), forskolin (a protein kinase-A activator), a combination of LiCl/forskolin, and LiCl/heparin (an IP₃ inhibitor) in order to identify the mechanisms involved in pigmentation. LiCl treatment resulted in ultrastructural and morphological alterations of melanophores. To identify the possible proteins responsible for this ultrastructural and morphological change, phosphorylation patterns in vitro and in vivo were analyzed. LiCl and LiCl/forskolin treatment elicited dramatic increases in the phosphorylation of a 55-kDa protein which was inhibited by heparin treatment. LiCl treatment also induced phosphorylation of a 55-kDa protein in melanophores purified from adult zebrafish. Collectively these results suggest that a LiCl-induced 55-kDa phosphoprotein plays a role in melanophore morphology and ultrastructure and ultimately effects gross pigmentation.

Deep sequencing plant defense responses

T get a genome-wide insight into the molecular events accompanying the emergence and the expansion, in Tunisia since 2001, of a severe multidrug-resistant tuberculosis (MDR-TB) outbreak, we sequenced and compared the genomes of two MDR outbreak strains and one phylogenetically closely related drug susceptible strain. With regard to the genome of the M. tuberculosis reference strain H37Rv, the 3 clinical strains shared 786 single nucleotide polymorphisms (SNPs) and 85 insertions/deletions (indels), a finding in favor of their close phylogenetic relationships. However, the drug-sensitive strain showed a consistent number of specific SNPs and indels and thus could not represent the immediate progenitor of the two MDR outbreak strains. Furthermore, and despite the fact that the two MDR outbreak strains display identical MIRU-VNTR24 patterns and differed only by one IS6110 copy, they could be differentiated by 49 SNPs and as much as 97 indels, a finding that may indicate a high level genomic instability during the outbreak expansion. Strikingly, some deletion events in functionally important genes shared by all the MDR outbreak strains were found to be restricted to the outbreak strain. These deletions could thus represent a critical step in the acquisition of the epidemic phenotype of the Tunisian MDR outbreak strain. In conclusion, comparative genomics disclosed the relative instability of the genome of an MDR M. tuberculosis outbreak strain and unraveled new clues that may lead to better understanding of its epidemic phenotype. Helmi Mardassi et al., J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.003I humans, RECQ1 is the most abundant of the five helicases (RECQ1, BLM, WRN, RECQL4, and RECQ5β) belonging to the RecQ family associated with rare genetic diseases of premature aging and cancer predisposition. Our earlier work has revealed a unique requirement of RECQ1 for genome stability maintenance. However, the mechanisms by which RECQ1 executes its functions in genome maintenance have remained largely elusive. My lab is utilizing an unbiased proteomic approach to identify novel protein interactions of RECQ1. We have discovered a direct interaction of RECQ1 with PARP-1 and characterized its functional implications in cellular response to oxidative stress. Moreover, we have identified that RECQ1 physically interacts and modulates the activity of Ku70/80 proteins which are part of DNA-PK complex for the repair of DNA double strand breaks. PARP-1 and DNA-PK are molecular targets for anti-cancer. Our results demonstrating RECQ1’s ability to modulate the activities of PARP-1 and Ku70/80 of DNA-PK complex suggest chemotherapeutic potential of RECQ1. RECQ1 is uniquely important for the proliferation of cancer cells. We have used quantitative chromatin immune-precipitation to show that replication stress induces specific enrichment of RECQ1 at common fragile sites FRA3B and FRA16D where replication forks have stalled following aphidicolin treatment. Fragile loci are fork stalling sites that occur naturally in genome and often coincide with chromosomal breakpoints in tumors. Current efforts are directed towards identifying what functional sub-modules of repair machinery are associated with RECQ1 at specific genomic loci and how it participates in dynamic response to challenges under genotoxic stress. Sudha Sharma, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002In this paper, we have design and augment an existing sentiment lexicon dictionary in the context of academic domain to provide academic community members facility to judge the quality of research articles by analyzing whether it has positive sentiments or negative sentiments. We have also developed a system which is able to identify opinionated words and phrases from the documents based on online dictionary such as WordNet. Our system uses SentiWordNet to assign sentiment scores to each word found in the document. Sentiments of words are assigned three sentiment scores: Positivity, Negativity and Objectivity with a word and lies in between the range of [0-1]. Our system provides user friendly interface to enable any member of the community to contribute in opinion lexicon generation by providing sentiment words and their polarity values.W investigate the function and regulation of proteins (14-3-3 isoforms in particular) involved in neurodegenerative diseases including Alzheimer’s and Parkinson’s. Our recent studies include G-substrate (named as a specific substrate of cGMPdependent protein kinase). It is a potent inhibitor of protein phosphatase 2A (PP2A) when phosphorylated on two threonines. Dopaminergic neurons of the substantia nigra, which express a higher level of G-substrate are less vulnerable to PD toxins than the adjacent A9 DA neurons. An mRNA for a shorter G-substrate variant has been described. Our database searches indicate that this variant is expressed only in humans. This may have implications for the current animal models of PD. We have compared the expression and function as inhibitor of PP2A of this variant (that retains one of the phosphothreonine motifs) It has a different specificity for protein interactions and may play an important role in the protection of DA neurons. We have identified novel G-substrate interacting proteins involved in PD. We have shown that G-substrate is degraded by the cysteine protease, DJ-1 (a causative gene for familial PD, also called “PARK-7”). DJ-1 may function only as a dimer and is responsive to oxidative stress. A DJ-1 Leu166Pro mutant predisposes the carriers to early onset PD and disrupts the function and dimerisation of the protein. We discovered that a drug used in the treatment of acute vertigo for over 40 years, but whose mechanism of action was unknown, interacts with DJ-1. Our initial results suggest that the drug protects against oxidative stress and we are analyzing the interaction in our drug development program. Alastair Aitken et al., J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004P cancer is the fourth leading cause of cancer deaths in the US. Through genome wide association studies (GWAS), we have identified multiple loci that significantly associate with risk of pancreatic cancer in individuals of European ancestry. One of these lies in a region on chromosome 5p15.33 that harbors the TERT and CLPTM1L genes, the former encoding the catalytic subunit of telomerase reverse transcriptase and the latter, which may play a role in apoptosis. This region has been identified in GWAS of at least nine cancers. To investigate the complex genetic architecture of this region, we have performed imputation and an agnostic subset based meta-analysis across 11 GWAS scans including 6 distinct cancers in over 60,000 subjects. We identified six independent risk loci in this region, five in the TERT gene and one in the neighboring CLPTM1L gene. Between 3-5 cancers mapped to each of the loci, with effects in both directions. Furthermore, we have investigated the CLPTM1L gene and its encoded protein and revealed a positive effect on growth in vitro and in vivo indicating a possible role in carcinogenesis. This effect was abrogated by deletion mutants of predicted functional domains of the protein. Through a proteomics screen we have identified protein partners for CLPTM1L and shown that it may play a role in cytokinesis. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, at a level not previously observed in other cancer susceptibility loci and indicate that CLPTM1L may play a role in cancer. Laufey Amundadottir, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004I this study, both gel-based two-dimensional fluorescent differential gel electrophoresis (2D-DIGE) and non-gel-based isobaric tags for relative and absolute quantitation (iTRAQ) coupled with liquid chromatography-tandem mass spectrometry have been used as screening tool for identification of differentially expressed proteins as potential biomarkers for oral malignant transformation. We comparatively analyzed the proteome profiles of multi-step tissues from normal epithelial tissues to premalignant oral leukoplakia (OLK) tissue and infiltrative oral squamous carcinoma(OSCC) tissues identically from three patients. In all, 1,465 unique proteins were identified. Of those, 240 were potentially differentially expressed between OSCC and normal tissues while 111 between normal and premalignant tissues, 202 between premalignant tissues and OSCC tissue. Subcellular location and functional annotation was done by Gene Ontology (GO). Pathway data was derived from KEGG and Biocater. Also of interest, we compared the different proteomic profiles between DIGE and iTRAQ. In general, nearly all the protein categories of DIGE was included in iTRAQ, but with different protein family members. The most significance is Annexin family, S100 calcium binding protein family, Heat shock protein family and keratins. Calcium regulation related proteins were validated by Western blotting and RT-PCR. Furthermore, up-regulation of those proteins was validated in OSCC tissue microarrays by immunohistochemistry. The correlation with malignant transformation as well as recurrence and disease-free survival of patients with OSCC also was estimated. Our study represents the successful complementary application with DIGE and iTRAQ to an investigation of oral malignant transformation, also provide valuable novel insights into the underlying mechanisms of oral carcinogenesis. Zhi Wang et al., J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004C analysis methodologies used in genome-wide association studies (GWAS) collapse the homozygous (i.e., A/A), hemizygous (i.e., A/0) and duplicative (i.e., A/A/A) genotype states at any given autosomal locus. This approach assumes that these classes of genotype are equivalent and treats the genotype variable itself as irreducible or unaltered by other co-occurring forms of genetic (e.g., structural) variation. However, our understanding of common, genome-wide copy number variation (CNV) clearly suggests that the construct of genotype may belie the enormous complexity of the genome. We provide here compelling evidence demonstrating the effect of co-occurring genetic variants on GWAS. We describe a new approach to association mapping, which we call copy number indexed GWAS (cni-GWAS). We show that properly accounting for allelic dosage can dramatically increase power to detect associations in genome-wide analysis of expression quantitative trait loci (eQTLs). A comprehensive study of trait-associated SNPs identified by GWAS shows them to be enriched, relative to allele frequency matched SNPs, for loci where allelic content is subject to altered dosage due to loss of chromosomal material. These findings have important implications for the analysis of all phenotypes and suggest that some portion of the “missing” heritability may be recovered by indexing SNPs according to copy number status. Lea K. Davis, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004A drug reactions (ADRs) are one of the major causes of patient morbidity and mortality. Pharmacogenetics is the study of how the genetic variations affect drug response in individual patients, while pharmacogenomics emphasizes the identification of the network of genes that govern drug response in individual patients using genome-wide approaches. Numerous genes, in particular those encoding drug metabolizing enzymes, drug transporters and drug targets, have been identified to affect drug response and ADRs. In the past decade, my laboratory has investigated the impact of polymorphisms of a number of important genes including CYP2B6, CYP2C9, ApoE, PXR/NR1I2, UGT1A1, GSTM1, GSTT1, GSTP1, TPMT, etc. on drug clearance, response, or ADRs. Mutations of these genes can significantly alter drug clearance, response or ADRs in different ethnic groups. In addition, mutations of certain genes can precipitate ADRs. Over the past years, genome-wide association studies (GWAS) have identified a number of common and rare variants that are associated with increased risk of ADRs. As affordable and reliable genetic testing tools become available to physicians, pharmacogenomics looks promising to facilitate individualization of drug therapy and as a result, this will maximize the therapeutic efficacy of drugs in patients while minimizing the occurrence of ADRs. Shu-Feng Zhou, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004K of the recombination landscape is central to understanding the molecular basis of recombination, population genetically-based inference and genome evolution. Studies have been limited, however, by the density of markers and the accuracy of sequencing. We sequenced many individuals from single meiosis and their parents in Arabidopsis, rice, bee and yeast, to close to 100% accuracy with markers ever few hundred bps. We identified large blocks of chromosome that were from either of two parents and so inferred the location of crossover events. Recombination blocks at the level of resolution (>500 kb) are randomly distributed on chromosomes in general. Unexpectedly, smaller recombination blocks (10-500 kb) are not only much more common than the larger blocks but are concentrated as recombination hot-spots. In addition we could identify small (<2 kb) gene conversion tracts. We estimate that well over 90% of recombination events are gene conversion events in plants. The rate of alteration of protein sequence owing to gene conversion is over 600 times that owing to mutation. In contrast, only a few events of gene conversion can be observed in bee, suggesting that gene conversion is less important in this anima. Surprisingly, some of small crossovers and gene conversions have occurred at the same position of chromosome in multiple individuals. On the whole, the rates of crossovers and gene conversions vary widely among species. Thus, our results demonstrate that different species have their own profiles of recombination, which could be essential for their haplotype diversity and their adaptation to new environments. Dacheng Tian, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002T requirement of self-defense in the ongoing struggle for survival led to the evolution of complex immune systems. About 500 million years ago two types of adaptive immune systems (AIS) arose in vertebrates which featured migratory populations of lymphocytes that express a diverse repertoire of recognition receptors. Jawed vertebrates somatically diversify the repertoire of immunoglobulin-domain based B and T cell antigen receptors through the rearrangement of V(D)J gene segments and somatic hypermutation, whereas an alternative AIS of jawless vartibrates (lamprey and hagfish) is based on variable lymphocyte receptors (VLRs) which diversify through recombinatorial usage of leucine-rich repeat (LRR) cassettes in VLR assembly. Three VLR genes have been identified; the VLRB gene is expressed by B-like lymphocytes, while VLRA and VLRC are expressed by two different lineages of T-like cells which in some ways resemble thymus-derived αβ and γδ T cells lymphocytes of jawed vertebrates. Analysis of the genomic organization of VLRA/VLRC has revealed shared usage of genomic donor cassettes during VLRA and VLRC assembly somewhat analogous to the shared usage of variable gene segments during TCRA/TCRD locus rearrangement in jawed vertebrates. The recent availability of the lamprey genome sequence may contribute to the reconstruction of VLR phylogeny and insight into how the adaptive immune function evolved in the context of well developed innate immunity. Sabyasachi Das, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002We have developed an invitro model system that consists of 300 human lymphoblastoid cell lines (LCLs) with extensive highthrough genomic data including genome wide SNPs, basal expression array, CpG methylation and microRNA data, together with drug cytotoxicity data to help identify candidate genes that might contribute to chemoresistance and response to targeted therapy and at the same time, to help understand the mechanisms involved in the variation in drug response. We have used this system to identify genes such as NT5C3 and FKBP5 that are important for response to cytidine analogues, gemcitabine and AraC, drugs that are commonly used to treat pancreatic, breast and hematological tumors. In addition, this system also allows us to validate biologically any signals identified during our clinical pharmacogenomic GWA studies. We have performed a GWAS using DNA samples from the largest breast cancer prevention trials, the NSABP P-1 and P-2 SERM (selective estrogen receptor modulator) prevention to identify markers that are associated with breast cancer risk after exposure to SERMs, tamoxifen and raloxifene. During the course of that study, we identified SNP signals in two genes, ZNF423 and CTSO showing that the risk alleles of these two SNP signals associated with Odds Ratio of 5.71 for breast cancer risk. Functional genomic studies further found a SNP dependent, estrogen or SERM dependent regulation of ZNF423 and CTSO expression, which is in parallel with the regulation of BRCA1 expression. These approaches using the LCL model let us to identify not only the potential candidate genes that could funciton as biomarkers for response to therapy but also help reveal novel biology underlying these genes and their involvement in regulation of important pathways in tumor growth and response to therapy.Processing applications with a large number of dimensions has been a challenge to the KDD (Knowledge Discovery and Data mining) community. An effective dimensionality reduction technique is an essential pre-processing method to remove noisy features. The proposed combined method for feature selection, where a filter based on correlation is applied on whole features set to find the relevant ones, and then, on these features a wrapper is applied in order to find the best features subset for a specified predictor. The high dimensionality of data can cause data overload, and if there are a lot of features, it is possible that the number of cases in data set to be insufficient for data mining operations. The solution for these problems is the reduction of data dimensions. The size of a data set is determined both by the number of cases and by the number of features considered for each case. In order to reduce number of cases one can use sampling or filtering. Feature reduction may be achieved either by feature composition or by feature selection. These methods should produce fewer features, so the algorithms can learn faster. Sometimes, even the accuracy of built models could be improved. Methods used for feature selection, can be classified as: filters, which are open loop methods, and wrappers, which are closed loop methods. As a possibility to reduce the number of feature considered by data mining algorithms, in order to make them more efficient, the combined method which uses a combination filter wrapper. The method used a correlation based filter on the whole set of features, then on relevant subset of features it used a wrapper which uses a decision tree classifier for prediction. The combined method achieved clearly superior performances for execution time, when we have used for feature selection the combined approach and backward selection as search strategy for wrapper. Biography M V Siva Prasad was awarded PhD degree from Nagarjuna University, Guntur. He received MTech [SE] from VTU, Belgaum and BE [CSE] from Gulbarga University. He is presently working as Professor/Principal in Anurag Engineering College (AEC), Ananthagiri(V), Kodad(M), Nalgonda(Dt.), Telangana, India. He has published more than 50 articles in various national/international journals. He has attended 2 international conferences organized ny IACSIT and got best paper awards.Data mining appears in the middle of the 1990s in the United States as a new discipline at the interface of Statistics and Information Technology: databases, artificial intelligence, machine learning. Along with advanced researches in health Domain monstrous of data are available, but the main difficulty is how to cultivate the existing information into a useful practices. Data mining has a great potential to enable healthcare systems to use data more effectively. Hence, DM improves care and reduces costs. In this paper, we used the various Data Mining techniques such as classification, logistic regression in health domain to predict Ischemic Stroke.W synteny visualization tools are important for sharing data and revealing patterns of complicated genome conservation and rearrangements. Such tools should allow biologists to upload genomic data for their own analysis. This requirement is critical because individual biologists are generating large amounts of genomic sequences that quickly overwhelm any centralized web resources to collect and display all those data. We have developed a web-based synteny viewer package, GSV/ mGSV, which was designed to satisfy the above requirement. GSV (http://cas-bioinfo.cas.unt.edu/gsv/) allows pair-wise genomic comparison, while mGSV (http://cas-bioinfo.cas.unt.edu/mgsv/) extends the comparison to multiple pairs of genomes. Users can upload their own genomic data files for visualization. Multiple genomes can be presented in a single integrated view with an enhanced user interface. Users can navigate through all the selected genomes in either pairwise or multiple viewing mode to examine conserved genomic regions as well as the accompanying genome annotations. Besides serving users who manually interact with the web server, Web Services were also provided for machine-to-machine communication to accept data sent by other remote resources. The entire GSV/mGSV package can also be downloaded for easy local installation. Qunfeng Dong, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002C number changes (CNV) cause an abnormal phenotype in 15% of cases with developmental delay. Typically, genomic changes are correlated with abnormalities at the “whole body” level, however, the functional consequences of CNVs at the cellular level, are rarely investigated. We are interested to determine if genes integral to CNVs show abnormal function in patient cells by testing their expression at the RNA and protein level and their known cellular functions. We identified abnormal cellular function of genes from CNVs from 1q21.1, 2p13.2 and Xq21.1. In case of the 1q21.1 CNV, the copy number change of its integral genes CHD1L and PRKAB2 resulted in perturbed chromatin remodeling and AMPK function, while in subjects with recurrent 2p13.2 CNV dysfunction of retinoic and notch signaling pathway implicated two genes from this CNV: CYP26B1 and EXOC6B, respectively. Finally, the CNV from Xq21.1 disrupted the MAGT1 gene, which has a role in Mg homeostasis, and resulted in reduced Mg influx in patient cells. Studying functional defects of CNVs is important as it identifies cellular pathways that are defective and offers treatment strategies to minimize their functional defects (e.g. restricted vitamin A diet in case of an abnormal retinoic acid metabolism in patients with 2p13.2 CNV or reducing the skin defects by adding Mg to the diet or as ointment in patients with MAGT1 CNV). Our work allows the establishment of a closer link between the genomic abnormality and its cellular and clinical consequences, and offers opportunities for treatment for some of the phenotypic defects. Evica Rajcan-Separovic, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002The collected EEG data corresponding to different cognitive states and emotional responses of the human subjects are used to feed the supervised learning models. The research relies on the Deep Learning models with different levels of depth. The task is to identify the most effective parameters of the learning procedure that would allow to reliably recognize such emotions, considered to be basic, as anger, disgust, fear, happiness, sadness, and surprise as well as their derivatives: amusement, contempt, contentment, embarrassment, excitement, guilt, pride in achievement, relief, satisfaction, sensory pleasure, and shame.Mutant hepatitis B with precore stop codon has been reported to be associated with severe liver damage in HBeAg negative patients with hepatocellular carcinoma. Clinically, the biological importance of pre-core G1896A mutation is not well established. The purpose of the present study was to determine hepatitis B virus genotypes and also to elucidate the association of G1896A mutation of precore gene and the severity of liver damage in HBV related HCC cases. Detection of HBV DNA sequences was carried out by polymerase chain reaction (PCR) using primers derived from the precore region of HBV genome. Ligase chain reaction (LCR) assay was performed to screen the presence or absence of G1896A mutation. Direct nucleotide sequencing was done to confirm the results of LCR. A total of 116 HBV related cases who attended the medical out patients department and wards of Lok Nayak Hospital, New Delhi, India were screened over the period of 3years. Patients having super-infection with HDV/ HCV/HIV and past history of interferon therapy were excluded. Sequence analysis of viral DNA established that the G1896A mutation was observed in 32 cases in HCC cases. Phylogenetic analysis revealed 60% isolates belonged to genotype A, while 20% belonged to genotype D and 20% belonged to genotype E. The present data suggests that precore G1896A mutations is responsible for 27.2% of the patients of Asian Indian origin suffering from HBV related HCC cases and these cases are more symptomatic and aggressive in patients with the mutant form of the virus as compared with the wild form.M and Pax7 are important myogenic regulators in animals. Our recent findings suggest that myostatin mutation changes Pax7 expression in muscle during fetus development. However, up to date, only the Erk1/2 signal is demonstrated to be involved in Pax7 expression by myostatin in myoblasts and satellite cells. Whether there are another pathways associated with Pax7 expression by myostatin or not remains unclear. In the present study, based on the differentially expressed genes from muscle transcriptome analysis between Textel and Ujumqin sheep, we builded the regulatory pathways from myostatin to Pax7 using the IPA platform. Quantitative RT-PCR analysis suggests that SRC, Histone h3, AKT, p38MAPK, BMI1, MYF5, MYOD, MYOG, and RB are associated with expression of Pax7 regulated by myostatin. To confirm the differential pathways through which myostatin regulates Pax7 between Texel and Ujumqin sheep, we constructed the lentiviral vector of siRNA for MSTN and performed the sheep myoblast proliferation and differentiation experiments, respectively. We show that myostatin inhibits the proliferative surge of sheep myoblasts ahead of time by increasing Pax7 transcription via the p38MAPK, Erk1/2, Akt, mTOR, and EZH2 signal pathways at mRNA and protein levels. On the other hand, myostatin promotes the sheep myoblast differentiation by down-regulating Pax7 transcription via the Erk1/2, p38MAPK, Akt, mTOR, EZH2, and SRC signals. Our findings expand the myogenic signals by which myostatin regulates Pax7 to affect the myogenic progression. We also indicate that myostatin participates in the epigenetic events during myoblast proliferation and differentiation. Hang-Xing Ren et al., J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004This study deals with the effects of an online search engine on the level of tourism through analyzing any change in the amount of searched information. The paper has the purpose to improve the forecast of tourism industry into South Korea by utilizing of Google Trends data which provide the data is provided in a relative query and time series format of data. This particular work attempts to analyze Google Trends based on with 3 specific keywords, “hotels, flights and tour” that are searched by potential tourists around the world from the world to South Korea. We conduct this study through a series of multiple regression models with one- month time-lag in order to forecast for easily forecasting performance. Accordingly, the findings suggest that Google Trends can be a good source of estimating tourism industry. Therefore, the business strategy makers in tourism industry related of South Korea can easily utilize of the Google Trends data for their future decisions.G (GB) is the most devastating type of human cancer, whereas a subset of the patients responds well to the current treatment modalities including temozolomide. Recent genetic profiling has revealed a mesenchymal subtype possesses the most aggressive characteristics among four genetic subtypes. To establish a more detailed sub-classification based on the protein level, we applied an antibody microarray targeting 165 signal transduction proteins to the human GB clinical materials, and found that the pluripotent stem-cell marker, alkaline phosphatase, and the epithelialmesenchymal transition (EMT) marker, Arf6, were most significantly up-regulated in the treatment-refractory GBs. These two factors highly correlated to each other, and also with expression of the putative gliomastem-like cell marker, CD133. Weused two-dimensional gel electrophoresis (2DE) combined with matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) to identify the proteins closely-related to tumor aggressiveness such as invasion and angiogenesis. Among the candidate proteins, the small GTP-binding proteins, Rac1 and RhoA which play a key role in cell motility and migration, were identified as a highly expressed protein in the patients with shorter survival, and significantly correlated with Arf6 expression. Plasminogen-activator inhibitor-1 (PAI-1), a protease contributing to modification of the extracellular matrix, has also found in the proteomic study, and its serum level can be used as a biomarker for tissue production. Since the expressions of PAI-1 and Arf6 were significantly correlated, EMT occurred in gliomatissues could be predicted pre-operatively. These multidisciplinary proteomic data obtained from the patients’ tumor tissues and sera collectively offer certain evidence that EMT linked with the stem-cell properties actually contribute to the aggressiveness of the human GB. Yasuo Iwadate, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002Although many anticancer drugs that target receptor tyrosine kinases (RTKs) provide clinical benefit, their long-term use is limited by resistance that is often attributed to increased abundance or activation of another RTK that compensates for the inhibited receptor. To uncover common and unique features in the signaling networks of RTKs, we measured time-dependent signaling in six isogenic cell lines, each expressing a different RTK as downstream proteins were systematically perturbed by RNA interference. Network models inferred from the data revealed a conserved set of signaling pathways and RTK-specific features that grouped the RTKs into three distinct classes: (i) an EGFR/FGFR1/c-Met class constituting epidermal growth factor receptor, fibroblast growth factor receptor 1, and the hepatocyte growth factor receptor c-Met; (ii) an IGF-1R/NTRK2 class constituting insulin-like growth factor 1 receptor and neurotrophic tyrosine receptor kinase 2; and (iii) a PDGFRβ class constituting platelet-derived growth factor receptor β. Analysis of cancer cell line data showed that many RTKs of the same class were coexpressed and that increasedB cancer is the number one invasive cancer of women. Endocrine therapy involving either the blockade of estrogen synthesis with aromatase inhibitors (AIs) or blockade of the estrogen receptor (ER) with selective estrogen receptor modulators (SERMs) represents a major advance in the treatment and prevention of breast cancer. We have conducted genome-wide association studies (GWAS) to identify genes associated with both musculo-skeletal adverse events that occur with the adjuvant AI therapy of postmenopausal women with ER(+) breast cancer and a separate study of women in whom breast cancer occurred during 5 years of preventive SERM therapy with tamoxifen or raloxifene. The single nucleotide polymorphism (SNP) signals and genes identified were then pursued with functional genomic and mechanistic studies. Both the results of these studies and the research strategy employed will be described in this presentation. Richard Weinshilboum, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002H C virus (HCV) is highly prevalent in Pakistan, and its infection can lead to chronic liver disease and hepatocellular carcinoma. The currently available treatment for treating HCV infection is not effective in all patients, has adverse side effects, and is not easily affordable. The aim of this study was to explore for the natural compounds that can inhibit the replication of Hepatitis C virus (HCV). Fluoroquinolones are the chemicals known as potent-active compounds that inhibit the replication of HCV genome by targeting its helicase protein NS3. Using 40 fluoroquinolones as reference molecules, a data set of 4000 natural products was screened that bore structural similarities with fluoroquinolone. From this data set, Random Forest classifier was used to predict active natural compounds that may have an inhibitory effect against HCV NS3 activity. This Random Forest classifier builds a set of decision trees by using a set of 0D, 1D, 2D, 3D and others, total 2080 molecular descriptors, of the two data sets i.e., the training and testing set. Compounds with RF score >0.5 are classified as an active compound against HCV. Using this approach, out of 4000 test molecules, 147 molecules were predicted to be active against HCV NS3 helicase. These predicted active compounds can be analyzed further using in silico and in vitro experimental models to discover an effective drug against HCV. The above-described approach is useful in discovering new, more portent and affordable drugs for treating HCV infection.M inverted repeat transposable elements (MITEs) are interesting transposable elements (TEs) because of their high copy numbers and mysterious identifies. Despite their low DNA content percentage in a genome, their numerous copies can disturb genomic stability and cause important genetic variations. Historically, MITE families were often discovered individually, a practice cannot keep pace with the large scale genome sequencing. Automated genome wide discovery of MITE families and their characterization are desirable. We developed a whole pipeline from MITE discovery to detailed analyses of MITEs at genomic scales. Using the pipeline, we performed in depth analyses of the MITE families in multiple recently release crop genomes. These analyses revealed the diversity of MITE families and their evolution in the host genome. We have also predicted the transposases that may be responsible for the mobilization of some MITE families. These MITE families can potentially be used as genetic markers for the improvement of these crop species. Guojun Yang, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004An extraordinary variation in mitochondrial genomes at within-species level exists in the angiosperm Silene vulgaris. The mitochondrial genomes of four analysed haplotypes of S. vulgaris show a distinct gene order, variable intergenic regions, they even differ in the number of coding genes. A high sequence variation in gene flanking regions among mitochondrial genomes is associated with the variation in regulatory motifs controlling the expression of mitochondrial genes. This polymorphism raises a question, how are the variable regulatory regions understood by various nuclear backgrounds. To provide the first insight, we have analyzed the transcription of the atp1 gene, encoding the subunit 1 of ATP synthase, a crucial enzyme in an energetic metabolism of a any eukaryotic cell. We found the variation in transcription profiles depending on the nuclear genes introduced by the pollen donor. We have generated the whole transcritome of S. vulgaris KOV based on SOLID data. We found numerous‘ islands of transcription‘ in intergenic regions, sometimes corresponding to predicted ORFs. In contrat, we detected very low expression of some genes (e.g. rpl5) suggesting that a nuclear copy took the leading role, despite of no sequence signs of pseudogenization. We have also produced the complete list of editing sites including intergenic regions and introns, which we called editome. The highly rearranged mitochondrial genomes with a diversity of cis- regulatory motifs make S. vulgaris an excellent model for the study of mitochondrial gene expression in plants.T determine the disease-causing allele(s) underlying human disease, high-throughput genomic methods are applied and provide thousands of gene variants per patient. We recently developed a novel approach, the “human gene connectome” (HGC) – a concept, method and database that describes the set of all in silico-predicted biologically plausible routes and distances between all pairs of human genes. With the HGC, we generated a “gene-specific connectome” for each human gene – the set of all human genes ranked by their predicted biological proximity to the core gene of interest, available at: http://lab.rockefeller. edu/casanova/HGC/. We demonstrated that the HGC is the most powerful approach for prioritizing high-throughput genetic variants in Mendelian disease studies. However, there is currently no effective gene-centric online interface for ranking genes by biological distance. We describe here the human gene connectome server (HGCS): a powerful, easy-to-use interactive online tool that enables researchers to prioritize any list of genes according to their biological proximity to core genes (i.e. genes that are known to be associated with the phenotype), and to predict novel gene pathways. We demonstrated the effectiveness of the HGCS for detecting herpes simplex encephalitis genes in patients’ whole exome sequencing data. The HGCS is freely available to use for non-commercial users at: http://hgc.rockefeller.edu/. Yuval Itan, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004G expression is highly regulated to ensure that each cell contains the correct complement of proteins necessary for proper cellular functions. During cell development, extensive ‘switch-like’ changes in gene expression occur through posttranscriptional regulation of mRNA. This includes changes in alternative mRNA splicing and polyadenylation, as well as regulation of mRNA stability and translation. Mutations which perturb cell-specific mRNA regulatory programs are associated with growing lists of human diseases, thus a greater understanding of how post-transcriptional mRNA regulatory networks are controlled in different cell types and stages of development is needed. The presentation will discuss the roles of RNA binding proteins in the regulation of gene expression in mammalian tissue development. In addition, the talk will describe how new biochemicalenrichment strategies combined with deep sequencing are providing new transcriptome-wide insights into mechanisms of posttranscriptional gene regulation in mammalian tissue development. Donny D. Licatalosi, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004T molecular mechanisms of Epstein-Barr virus (EBV)-associated gastric cancer remains largely unclear. We applied integrative genomic approaches to uncover EBV-associated genomic and epigenomic variations in gastric cancer. Whole genome, transcriptome and epigenome sequencing was performed in EBV-infected AGS cells (AGS-EBV) and its parental EBV-negative AGS cells. The identified novel mutations and epigenetic alterations by genome sequencing were verified and characterized in 134 primary gastric cancers with (n=34) or without (n=100) EBV infection. Transcriptome analysis of AGS-EBV revealed expression of 9 well-known and 71 un-reported EBV genes in gastric cancer, top 10 of which were recapitulated in primary EBV(+) gastric cancers. Whole genome sequencing identified 45 novel EBV-associated non-synonymous mutations. Novel mutated genes were validated to be significantly associated with EBV(+) gastric cancers, including AKT2 (P<0.0001), CCNA1 (P=0.004), MAP3K4 (P<0.05) and TGFBR1 (P<0.05). Notably, AKT2 mutation was associated with poorer survival in EBV(+) gastric cancer patients (P=0.006). Integration of epigenome and transcriptome analyses identified 216 genes transcriptionally downregulated by EBVassociated promoter methylation. Novel downregulated genes including ACSS1, FAM3B, IHH and TRABD were confirmed to be significantly methylated in primary EBV(+) gastric cancers. Moreover, KEGG pathway enrichment analysis revealed five intercorrelated pathways (axon guidance, focal adhesion, cytokine-cytokine receptor interaction, MAPK signaling and regulation of actin cytoskeleton) being commonly affected by EBV-associated genomic and epigenomic alterations. These data provide an extensive and high-quality genomic landmark for EBV-associated gastric cancer and demonstrate the novel genomic and epigenomic abnormalities and signaling networks that may govern EBV-associated gastric carcinogenesis. Qiaoyi Liang, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002T recent sequencing of more than 1000 human genomes has revealed that two individuals from the same population have millions of genomic variations between them. Closely located mutations are linked together forming haplotypes that change constantly due to recombination events during gametogenesis. Evolution occurs on whole ensembles of these numerous haplotypes, where mutations influence each other and should be considered as a whole entity – a gigantic matrix, unique for every individual genome. Several mathematical theories have attempted to describe the intricate dynamics of genomic variations in populations. However, these theories are conflicting with each other, and there is no universally acknowledged understanding of genome evolution. We attempted to model mammalian population genetics using a pure computational approach, taking advantage of the enormous power of modern supercomputers. A software package named Matrix Algorithms for Genome Evolution (MAGE), has been created and tested for modeling evolution of entire chromosomes. We have validated that MAGE can precisely mimic real biological processes that have influence on genome evolution such as: 1. Authentic arrangements of genes and functional genomics elements; 2. Frequencies of various types of mutations in different nucleotide contexts; 3. Non-random distribution of meiotic recombination events along chromosomes. Computer modeling with MAGE made a breakthrough in the appreciation of mutation dynamics. In particular, we demonstrated that a numeric parameter, a number of DNA recombination events per gamete, is crucial factor that influence the population fitness under the observed intense flow of novel mutations (~50 mutations per individual). MAGE can compute the probability of fixation for a mutation with a selection coefficient s as a function of multiple parameters; 1) mutation influx and the distribution of novel mutations by their selection coefficients; 2) selection pressure (including number of offspring per individual, mating schemes, population size); 3) genomic parameters (such as number of meiotic recombinations, arrangements of genes and their degrees of dominance). Alexei Fedorov, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.002A 538 protein kinases catalyze the phosphorylation of as many as 970,000 phosphosites in the human phosphoproteome. Over a third of global pharmaceutical R&D is focused on the discovery and development of protein kinases inhibitors, since defects in signalling from these enzymes has been linked to over 400 diseases. Using predictive algorithms based on training with over 22,000 kinase-substrate and 105,000 kinase-drug pairs along with the primary structures of the ~250 amino acid catalytic domains of 492 human protein kinases, we have defined many amino acid residues in these enzymes that are critical for determining their catalytic activity, substrate specificity and drug sensitivity. With the existence of about 60 million single nucleotide polymorphisms in human genomes, predictions based on this kind of information will be required to identify those individuals that harbour disease-causing mutations and the most effective drugs that may offer the best recourses in a personalized medicine strategy. We have also undertaken evolutionary analyses of the 970,000 phosphosites to identify the most conserved in 20 other diverse species to aid in the construction of a tissue and cell-specific atlas of high resolution maps of the interactions of the most critical nodes of communication in cell signalling networks. We have used this information to produce hundreds of antibodies against these protein and phosphosite targets that are deployed in high density antibody microarrays to permit wide scale monitoring of signalling systems in specific tissue and cell biopsy samples. The prediction and experimental data provided by these studies have been made freely available in a suite of open-access dataand knowledge-bases that are accessible from www. kinexus.ca. Steven Pelech, J Data Mining Genomics Proteomics 2013, 4:5 http://dx.doi.org/10.4172/2153-0602.S1.004Genome-wide pharmacogenomic studies for developing targeted therapies offer the advantage of hypothesis-free search for tentative drug response biomarkers (efficacy and safety). However, they require large patient cohorts and are therefore laborious and quite costly. Here we present our experience with an alternative approach, based on genome-wide transcriptomic profiling of a panel of human lymphoblastoid cell lines (LCLs) representing unrelated healthy donors. LCLs can be obtained from most large biobanks and our approach offer simple and inexpensive discovery of tentative drug response biomarkers. The expression of candidate biomarker genes and microRNAs (miRNAs) is subsequently measured by qPCR in blood samples of patient cohorts. We applied genome-wide expression profiling of human LCLs for searching tentative SSRI antidepressant drug response biomarkers. Eighty LCLs from healthy adult female individuals were phenotyped for growth inhibition by paroxetine. Fourteen LCLs were chosen for comparative expression profiling with Affymetrix microarrays. The most notable difference between LCLs displaying high vs. low paroxetine sensitivities was a 6.3-fold lower basal expression (p=0.0000256) of CHL1 (close homologue of L1), coding for neuronal cell adhesion protein implicated in thalamocortical circuitry. This was confirmed by qPCR. Next, our studies with commercial miRNA arrays have identified miR-151-3p, predicted to target CHL1, as an additional biomarker for SSRI sensitivity. Other miRNAs showing differential expression levels in the two groups of human LCLs, which corresponds with the differential expression of other tentative biomarker genes, included miR-132, miR-212, miR-30b* (miR-30b-3p), let-7b and let-7c, all of which are also implicated in CNS function. Findings will be presented from our ongoing studies with DNA samples from major depression patients with known SSRI response phenotypes. In vitro drug sensitivity phenotyping of LCLs from unrelated donors, followed by their genome-wide expression profiling for both genes and miRNAs, appears to be a powerful and cost-effective tool for early studies on tentative drug response biomarkers (prior to collection of clinical samples) for aiding clinical trial design. The method is applicable for any CNS drug whose target is functionally expressed by LCLs. This approach builds upon the utility of LCLs of healthy donors to faithfully represent the complex human genomic and epigenomic repertoire. gurwitz@post.tau.ac.il