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Dive into the research topics where Vishalakshi Nanjappa is active.

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Featured researches published by Vishalakshi Nanjappa.


Nature | 2014

A draft map of the human proteome

Min Sik Kim; Sneha M. Pinto; Derese Getnet; Raja Sekhar Nirujogi; Srikanth S. Manda; Raghothama Chaerkady; Dhanashree S. Kelkar; Ruth Isserlin; Shobhit Jain; Joji Kurian Thomas; Babylakshmi Muthusamy; Pamela Leal-Rojas; Praveen Kumar; Nandini A. Sahasrabuddhe; Lavanya Balakrishnan; Jayshree Advani; Bijesh George; Santosh Renuse; Lakshmi Dhevi N. Selvan; Arun H. Patil; Vishalakshi Nanjappa; Aneesha Radhakrishnan; Samarjeet Prasad; Tejaswini Subbannayya; Rajesh Raju; Manish Kumar; Sreelakshmi K. Sreenivasamurthy; Arivusudar Marimuthu; Gajanan Sathe; Sandip Chavan

The availability of human genome sequence has transformed biomedical research over the past decade. However, an equivalent map for the human proteome with direct measurements of proteins and peptides does not exist yet. Here we present a draft map of the human proteome using high-resolution Fourier-transform mass spectrometry. In-depth proteomic profiling of 30 histologically normal human samples, including 17 adult tissues, 7 fetal tissues and 6 purified primary haematopoietic cells, resulted in identification of proteins encoded by 17,294 genes accounting for approximately 84% of the total annotated protein-coding genes in humans. A unique and comprehensive strategy for proteogenomic analysis enabled us to discover a number of novel protein-coding regions, which includes translated pseudogenes, non-coding RNAs and upstream open reading frames. This large human proteome catalogue (available as an interactive web-based resource at http://www.humanproteomemap.org) will complement available human genome and transcriptome data to accelerate biomedical research in health and disease.


Genome Biology | 2010

NetPath: a public resource of curated signal transduction pathways.

Kumaran Kandasamy; S. Sujatha Mohan; Rajesh Raju; Shivakumar Keerthikumar; Ghantasala S. Sameer Kumar; Abhilash Venugopal; Deepthi Telikicherla; Daniel J. Navarro; Suresh Mathivanan; Christian Pecquet; Sashi Kanth Gollapudi; Sudhir Gopal Tattikota; Shyam Mohan; Hariprasad Padhukasahasram; Yashwanth Subbannayya; Renu Goel; Harrys K.C. Jacob; Jun Zhong; Raja Sekhar; Vishalakshi Nanjappa; Lavanya Balakrishnan; Roopashree Subbaiah; Yl Ramachandra; B. Abdul Rahiman; T. S. Keshava Prasad; Jian Xin Lin; Jon C. D. Houtman; Stephen Desiderio; Jean-Christophe Renauld; Stefan N. Constantinescu

We have developed NetPath as a resource of curated human signaling pathways. As an initial step, NetPath provides detailed maps of a number of immune signaling pathways, which include approximately 1,600 reactions annotated from the literature and more than 2,800 instances of transcriptionally regulated genes - all linked to over 5,500 published articles. We anticipate NetPath to become a consolidated resource for human signaling pathways that should enable systems biology approaches.


Nucleic Acids Research | 2014

Plasma Proteome Database as a resource for proteomics research: 2014 update.

Vishalakshi Nanjappa; Joji Kurian Thomas; Arivusudar Marimuthu; Babylakshmi Muthusamy; Aneesha Radhakrishnan; Rakesh K. Sharma; Aafaque Ahmad Khan; Lavanya Balakrishnan; Nandini A. Sahasrabuddhe; Satwant Kumar; Binit N Jhaveri; Kaushal Vinaykumar Sheth; Ramesh Kumar Khatana; Patrick G. Shaw; S. Srikanth; Premendu P. Mathur; Subramanian Shankar; Dindagur Nagaraja; Rita Christopher; Suresh Mathivanan; Rajesh Raju; Ravi Sirdeshmukh; Aditi Chatterjee; Richard J. Simpson; H. C. Harsha; Akhilesh Pandey; T. S. Keshava Prasad

Plasma Proteome Database (PPD; http://www.plasmaproteomedatabase.org/) was initially described in the year 2005 as a part of Human Proteome Organization’s (HUPO’s) pilot initiative on Human Plasma Proteome Project. Since then, improvements in proteomic technologies and increased throughput have led to identification of a large number of novel plasma proteins. To keep up with this increase in data, we have significantly enriched the proteomic information in PPD. This database currently contains information on 10 546 proteins detected in serum/plasma of which 3784 have been reported in two or more studies. The latest version of the database also incorporates mass spectrometry-derived data including experimentally verified proteotypic peptides used for multiple reaction monitoring assays. Other novel features include published plasma/serum concentrations for 1278 proteins along with a separate category of plasma-derived extracellular vesicle proteins. As plasma proteins have become a major thrust in the field of biomarkers, we have enabled a batch-based query designated Plasma Proteome Explorer, which will permit the users in screening a list of proteins or peptides against known plasma proteins to assess novelty of their data set. We believe that PPD will facilitate both clinical and basic research by serving as a comprehensive reference of plasma proteins in humans and accelerate biomarker discovery and translation efforts.


Journal of Proteome Research | 2011

A comprehensive map of the human urinary proteome.

Arivusudar Marimuthu; Robert N. O’Meally; Raghothama Chaerkady; Yashwanth Subbannayya; Vishalakshi Nanjappa; Praveen Kumar; Dhanashree S. Kelkar; Sneha M. Pinto; Rakesh Sharma; Santosh Renuse; Renu Goel; Rita Christopher; Bernard Delanghe; Robert N. Cole; H. C. Harsha; Akhilesh Pandey

The study of the human urinary proteome has the potential to offer significant insights into normal physiology as well as disease pathology. The information obtained from such studies could be applied to the diagnosis of various diseases. The high sensitivity, resolution, and mass accuracy of the latest generation of mass spectrometers provides an opportunity to accurately catalog the proteins present in human urine, including those present at low levels. To this end, we carried out a comprehensive analysis of human urinary proteome from healthy individuals using high-resolution Fourier transform mass spectrometry. Importantly, we used the Orbitrap for detecting ions in both MS (resolution 60 000) and MS/MS (resolution 15 000) modes. To increase the depth of our analysis, we characterized both unfractionated as well as lectin-enriched proteins in our experiments. In all, we identified 1,823 proteins with less than 1% false discovery rate, of which 671 proteins have not previously been reported as constituents of human urine. This data set should serve as a comprehensive reference list for future studies aimed at identification and characterization of urinary biomarkers for various diseases.


Proteomics | 2011

Comprehensive proteomic analysis of human bile

Mustafa A. Barbhuiya; Nandini A. Sahasrabuddhe; Sneha M. Pinto; Babylakshmi Muthusamy; Tekcham Dinesh Singh; Vishalakshi Nanjappa; Shivakumar Keerthikumar; Bernard Delanghe; H. C. Harsha; Raghothama Chaerkady; Visvajit Jalaj; Sanjeev Gupta; Braj Raj Shrivastav; Pramod Kumar Tiwari; Akhilesh Pandey

Bile serves diverse functions from metabolism to transport. In addition to acids and salts, bile is composed of proteins secreted or shed by the hepatobiliary system. Although there have been previous efforts to catalog biliary proteins, an in‐depth analysis of the bile proteome has not yet been reported. We carried out fractionation of non‐cancerous bile samples using a multipronged approach (SDS‐PAGE, SCX and OFFGEL) followed by MS analysis on an LTQ‐Orbitrap Velos mass spectrometer using high resolution at both MS and MS/MS levels. We identified 2552 proteins – the largest number of proteins reported in human bile till date. To our knowledge, there are no previous studies employing high‐resolution MS reporting a more detailed catalog of any body fluid proteome in a single study. We propose that extensive fractionation coupled to high‐resolution MS can be used as a standard methodology for in‐depth characterization of any body fluid. This catalog should serve as a baseline for the future studies aimed at discovering biomarkers from bile in gallbladder, hepatic, and biliary cancers.


Database | 2011

A comprehensive manually curated reaction map of RANKL/RANK-signaling pathway.

Rajesh Raju; Lavanya Balakrishnan; Vishalakshi Nanjappa; Mitali Bhattacharjee; Derese Getnet; Babylakshmi Muthusamy; Joji Kurian Thomas; Jyoti Sharma; B. Abdul Rahiman; H. C. Harsha; Subramanian Shankar; T. S. Keshava Prasad; S. Sujatha Mohan; Gary D. Bader; Mohan R. Wani; Akhilesh Pandey

Receptor activator of nuclear factor-kappa B ligand (RANKL) is a member of tumor necrosis factor (TNF) superfamily that plays a key role in the regulation of differentiation, activation and survival of osteoclasts and also in tumor cell migration and bone metastasis. Osteoclast activation induced by RANKL regulates hematopoietic stem cell mobilization as part of homeostasis and host defense mechanisms thereby linking regulation of hematopoiesis with bone remodeling. Binding of RANKL to its receptor, Receptor activator of nuclear factor-kappa B (RANK) activates molecules such as NF-kappa B, mitogen activated protein kinase (MAPK), nuclear factor of activated T cells (NFAT) and phosphatidyl 3-kinase (PI3K). Although the molecular and cellular roles of these molecules have been reported previously, a systematic cataloging of the molecular events induced by RANKL/RANK interaction has not been attempted. Here, we present a comprehensive reaction map of the RANKL/RANK-signaling pathway based on an extensive manual curation of the published literature. We hope that the curated RANKL/RANK-signaling pathway model would enable new biomedical discoveries, which can provide novel insights into disease processes and development of novel therapeutic interventions. Database URL: http://www.netpath.org/pathways?path_id=NetPath_21


Molecular & Cellular Proteomics | 2014

Annotation of the Zebrafish Genome through an Integrated Transcriptomic and Proteomic Analysis

Dhanashree S. Kelkar; Elayne Provost; Raghothama Chaerkady; Babylakshmi Muthusamy; Srikanth S. Manda; Tejaswini Subbannayya; Lakshmi Dhevi N. Selvan; Chieh-Huei Wang; Keshava K. Datta; Sunghee Woo; Sutopa B. Dwivedi; Santosh Renuse; Derese Getnet; Tai Chung Huang; Min-Sik Kim; Sneha M. Pinto; Christopher J. Mitchell; Praveen Kumar; Jyoti Sharma; Jayshree Advani; Gourav Dey; Lavanya Balakrishnan; Nazia Syed; Vishalakshi Nanjappa; Yashwanth Subbannayya; Renu Goel; T. S. Keshava Prasad; Vineet Bafna; Ravi Sirdeshmukh; Harsha Gowda

Accurate annotation of protein-coding genes is one of the primary tasks upon the completion of whole genome sequencing of any organism. In this study, we used an integrated transcriptomic and proteomic strategy to validate and improve the existing zebrafish genome annotation. We undertook high-resolution mass-spectrometry-based proteomic profiling of 10 adult organs, whole adult fish body, and two developmental stages of zebrafish (SAT line), in addition to transcriptomic profiling of six organs. More than 7,000 proteins were identified from proteomic analyses, and ∼69,000 high-confidence transcripts were assembled from the RNA sequencing data. Approximately 15% of the transcripts mapped to intergenic regions, the majority of which are likely long non-coding RNAs. These high-quality transcriptomic and proteomic data were used to manually reannotate the zebrafish genome. We report the identification of 157 novel protein-coding genes. In addition, our data led to modification of existing gene structures including novel exons, changes in exon coordinates, changes in frame of translation, translation in annotated UTRs, and joining of genes. Finally, we discovered four instances of genome assembly errors that were supported by both proteomic and transcriptomic data. Our study shows how an integrative analysis of the transcriptome and the proteome can extend our understanding of even well-annotated genomes.


Journal of Signal Transduction | 2012

A Bioinformatics Resource for TWEAK-Fn14 Signaling Pathway

Mitali Bhattacharjee; Rajesh Raju; Aneesha Radhakrishnan; Vishalakshi Nanjappa; Babylakshmi Muthusamy; Kamlendra Singh; Dheebika Kuppusamy; Bhavya Teja Lingala; Archana Pan; Premendu P. Mathur; H. C. Harsha; T. S. Keshava Prasad; Gerald J. Atkins; Akhilesh Pandey; Aditi Chatterjee

TNF-related weak inducer of apoptosis (TWEAK) is a new member of the TNF superfamily. It signals through TNFRSF12A, commonly known as Fn14. The TWEAK-Fn14 interaction regulates cellular activities including proliferation, migration, differentiation, apoptosis, angiogenesis, tissue remodeling and inflammation. Although TWEAK has been reported to be associated with autoimmune diseases, cancers, stroke, and kidney-related disorders, the downstream molecular events of TWEAK-Fn14 signaling are yet not available in any signaling pathway repository. In this paper, we manually compiled from the literature, in particular those reported in human systems, the downstream reactions stimulated by TWEAK-Fn14 interactions. Our manual amassment of the TWEAK-Fn14 pathway has resulted in cataloging of 46 proteins involved in various biochemical reactions and TWEAK-Fn14 induced expression of 28 genes. We have enabled the availability of data in various standard exchange formats from NetPath, a repository for signaling pathways. We believe that this composite molecular interaction pathway will enable identification of new signaling components in TWEAK signaling pathway. This in turn may lead to the identification of potential therapeutic targets in TWEAK-associated disorders.


Database | 2011

NetSlim: high-confidence curated signaling maps

Rajesh Raju; Vishalakshi Nanjappa; Lavanya Balakrishnan; Aneesha Radhakrishnan; Joji Kurian Thomas; Jyoti Sharma; Maozhen Tian; Shyam Mohan Palapetta; Tejaswini Subbannayya; Nirujogi Raja Sekhar; Babylakshmi Muthusamy; Renu Goel; Yashwanth Subbannayya; Deepthi Telikicherla; Mitali Bhattacharjee; Sneha M. Pinto; Nazia Syed; Manda Srinivas Srikanth; Gajanan Sathe; Sartaj Ahmad; Sandip Chavan; Ghantasala S. Sameer Kumar; Arivusudar Marimuthu; T. S. K. Prasad; H. C. Harsha; B. Abdul Rahiman; Osamu Ohara; Gary D. Bader; S. Sujatha Mohan; William P. Schiemann

We previously developed NetPath as a resource for comprehensive manually curated signal transduction pathways. The pathways in NetPath contain a large number of molecules and reactions which can sometimes be difficult to visualize or interpret given their complexity. To overcome this potential limitation, we have developed a set of more stringent curation and inclusion criteria for pathway reactions to generate high-confidence signaling maps. NetSlim is a new resource that contains this ‘core’ subset of reactions for each pathway for easy visualization and manipulation. The pathways in NetSlim are freely available at http://www.netpath.org/netslim. Database URL: www.netpath.org/netslim


Cancer Biology & Therapy | 2014

Pancreatic Cancer Database: An integrative resource for pancreatic cancer

Joji Kurian Thomas; Min Sik Kim; Lavanya Balakrishnan; Vishalakshi Nanjappa; Rajesh Raju; Arivusudar Marimuthu; Aneesha Radhakrishnan; Babylakshmi Muthusamy; Aafaque Ahmad Khan; Sruthi Sakamuri; Shantal Gupta Tankala; Mukul Singal; Bipin G. Nair; Ravi Sirdeshmukh; Aditi Chatterjee; T. S. Keshava Prasad; Anirban Maitra; Harsha Gowda; Ralph H. Hruban; Akhilesh Pandey

Pancreatic cancer is the fourth leading cause of cancer-related death in the world. The etiology of pancreatic cancer is heterogeneous with a wide range of alterations that have already been reported at the level of the genome, transcriptome, and proteome. The past decade has witnessed a large number of experimental studies using high-throughput technology platforms to identify genes whose expression at the transcript or protein levels is altered in pancreatic cancer. Based on expression studies, a number of molecules have also been proposed as potential biomarkers for diagnosis and prognosis of this deadly cancer. Currently, there are no repositories which provide an integrative view of multiple Omics data sets from published research on pancreatic cancer. Here, we describe the development of a web-based resource, Pancreatic Cancer Database (http://www.pancreaticcancerdatabase.org), as a unified platform for pancreatic cancer research. PCD contains manually curated information pertaining to quantitative alterations in miRNA, mRNA, and proteins obtained from small-scale as well as high-throughput studies of pancreatic cancer tissues and cell lines. We believe that PCD will serve as an integrative platform for scientific community involved in pancreatic cancer research.

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Akhilesh Pandey

Johns Hopkins University School of Medicine

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David Sidransky

Johns Hopkins University School of Medicine

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Santosh Renuse

Amrita Vishwa Vidyapeetham

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Bipin G. Nair

Amrita Vishwa Vidyapeetham

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