Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Manhong Dai is active.

Publication


Featured researches published by Manhong Dai.


Nucleic Acids Research | 2005

Evolving gene/transcript definitions significantly alter the interpretation of GeneChip data

Manhong Dai; Pinglang Wang; Andrew D. Boyd; Georgi Kostov; Brian D. Athey; Edward G. Jones; William E. Bunney; Richard M. Myers; Terry Speed; Huda Akil; Stanley J. Watson; Fan-Dong Meng

Genome-wide expression profiling is a powerful tool for implicating novel gene ensembles in cellular mechanisms of health and disease. The most popular platform for genome-wide expression profiling is the Affymetrix GeneChip. However, its selection of probes relied on earlier genome and transcriptome annotation which is significantly different from current knowledge. The resultant informatics problems have a profound impact on analysis and interpretation the data. Here, we address these critical issues and offer a solution. We identified several classes of problems at the individual probe level in the existing annotation, under the assumption that current genome and transcriptome databases are more accurate than those used for GeneChip design. We then reorganized probes on more than a dozen popular GeneChips into gene-, transcript- and exon-specific probe sets in light of up-to-date genome, cDNA/EST clustering and single nucleotide polymorphism information. Comparing analysis results between the original and the redefined probe sets reveals ∼30–50% discrepancy in the genes previously identified as differentially expressed, regardless of analysis method. Our results demonstrate that the original Affymetrix probe set definitions are inaccurate, and many conclusions derived from past GeneChip analyses may be significantly flawed. It will be beneficial to re-analyze existing GeneChip data with updated probe set definitions.


intelligent systems in molecular biology | 2006

SNP Function Portal

Pinglang Wang; Manhong Dai; Weijian Xuan; Richard C. McEachin; Anne U. Jackson; Laura J. Scott; Brian D. Athey; Stanley J. Watson; Fan Meng

MOTIVATION Finding the potential functional significance of SNPs is a major bottleneck in understanding genome-wide SNP scanning results, as the related functional data are distributed across many different databases. The SNP Function Portal is designed to be a clearing house for all public domain SNP functional annotation data, as well as in-house functional annotations derived from different data sources. It currently contains SNP functional annotations in six major categories including genomic elements, transcription regulation, protein function, pathway, disease and population genetics. Besides extensive SNP functional annotations, the SNP Function Portal includes a powerful search engine that accepts different types of genetic markers as input and identifies all genetically related SNPs based on the HapMap Phase II data as well as the relationship of different markers to known genes. As a result, our system allows users to identify the potential biological impact of genetic markers and complex relationships among genetic markers and genes, and it greatly facilitates knowledge discovery in genome-wide SNP scanning experiments. AVAILABILITY http://brainarray.mbni.med.umich.edu/Brainarray/Database/SearchSNP/snpfunc.aspx.


Frontiers in Genetics | 2013

G protein-linked signaling pathways in bipolar and major depressive disorders

Hiroaki Tomita; Mary E. Ziegler; Helen B. Kim; Simon J. Evans; Prabhakara V. Choudary; Jun Li; Fan Meng; Manhong Dai; Richard M. Myers; Charles R. Neal; Terry Speed; Jack D. Barchas; Alan F. Schatzberg; Stanley J. Watson; Huda Akil; Edward G. Jones; William E. Bunney; Marquis P. Vawter

The G-protein linked signaling system (GPLS) comprises a large number of G-proteins, G protein-coupled receptors (GPCRs), GPCR ligands, and downstream effector molecules. G-proteins interact with both GPCRs and downstream effectors such as cyclic adenosine monophosphate (cAMP), phosphatidylinositols, and ion channels. The GPLS is implicated in the pathophysiology and pharmacology of both major depressive disorder (MDD) and bipolar disorder (BPD). This study evaluated whether GPLS is altered at the transcript level. The gene expression in the dorsolateral prefrontal (DLPFC) and anterior cingulate (ACC) were compared from MDD, BPD, and control subjects using Affymetrix Gene Chips and real time quantitative PCR. High quality brain tissue was used in the study to control for confounding effects of agonal events, tissue pH, RNA integrity, gender, and age. GPLS signaling transcripts were altered especially in the ACC of BPD and MDD subjects. Transcript levels of molecules which repress cAMP activity were increased in BPD and decreased in MDD. Two orphan GPCRs, GPRC5B and GPR37, showed significantly decreased expression levels in MDD, and significantly increased expression levels in BPD. Our results suggest opposite changes in BPD and MDD in the GPLS, “activated” cAMP signaling activity in BPD and “blunted” cAMP signaling activity in MDD. GPRC5B and GPR37 both appear to have behavioral effects, and are also candidate genes for neurodegenerative disorders. In the context of the opposite changes observed in BPD and MDD, these GPCRs warrant further study of their brain effects.


Bioinformatics | 2007

Web-based GeneChip analysis system for large-scale collaborative projects

Manhong Dai; Pinglang Wang; Elvis Jakupovic; Stanley J. Watson; Fan Meng

UNLABELLED The Web-Based GeneChip Analysis System (WGAS) is developed to overcome limitations in analysis setup efficiency, data and procedure sharing, as well as security issues in existing commercial and public domain solutions. It also incorporates unique functions and resources for more accurate and flexible GeneChip analysis. AVAILABILITY WGAS is freely available at: http://arrayanalysis.mbni.med.umich.edu/arrayanalysis.html.


BMC Bioinformatics | 2009

Open Biomedical Ontology-based Medline exploration

Weijian Xuan; Manhong Dai; Barbara Mirel; Jean Song; Brian D. Athey; Stanley J. Watson; Fan Meng

BackgroundEffective Medline database exploration is critical for the understanding of high throughput experimental results and the development of novel hypotheses about the mechanisms underlying the targeted biological processes. While existing solutions enhance Medline exploration through different approaches such as document clustering, network presentations of underlying conceptual relationships and the mapping of search results to MeSH and Gene Ontology trees, we believe the use of multiple ontologies from the Open Biomedical Ontology can greatly help researchers to explore literature from different perspectives as well as to quickly locate the most relevant Medline records for further investigation.ResultsWe developed an ontology-based interactive Medline exploration solution called PubOnto to enable the interactive exploration and filtering of search results through the use of multiple ontologies from the OBO foundry. The PubOnto program is a rich internet application based on the FLEX platform. It contains a number of interactive tools, visualization capabilities, an open service architecture, and a customizable user interface. It is freely accessible at: http://brainarray.mbni.med.umich.edu/brainarray/prototype/pubonto.


computational systems bioinformatics | 2007

Supercomputing with toys: harnessing the power of NVIDIA 8800GTX and playstation 3 for bioinformatics problem.

Justin Wilson; Manhong Dai; Elvis Jakupovic; Stanley J. Watson; Fan Meng

Modern video cards and game consoles typically have much better performance to price ratios than that of general purpose CPUs. The parallel processing capabilities of game hardware are well-suited for high throughput biomedical data analysis. Our initial results suggest that game hardware is a cost-effective platform for some computationally demanding bioinformatics problems.


Journal of Psychiatric Research | 2016

The microRNA network is altered in anterior cingulate cortex of patients with unipolar and bipolar depression

Joshua A. Azevedo; Bradley S. Carter; Fan Meng; David L. Turner; Manhong Dai; Alan F. Schatzberg; Jack D. Barchas; Edward G. Jones; William E. Bunney; Richard M. Myers; Huda Akil; Stanley J. Watson; Robert C. Thompson

MicroRNAs (miRNAs) are small, non-coding RNAs acting as post-transcriptional regulators of gene expression. Though implicated in multiple CNS disorders, miRNAs have not been examined in any psychiatric disease state in anterior cingulate cortex (AnCg), a brain region centrally involved in regulating mood. We performed qPCR analyses of 29 miRNAs previously implicated in psychiatric illness (major depressive disorder (MDD), bipolar disorder (BP) and/or schizophrenia (SZ)) in AnCg of patients with MDD and BP versus controls. miR-132, miR-133a and miR-212 were initially identified as differentially expressed in BP, miR-184 in MDD and miR-34a in both MDD and BP (although none survived multiple correction testing and must be considered preliminary). In silico target prediction algorithms identified putative targets of differentially expressed miRNAs. Nuclear Co-Activator 1 (NCOA1), Nuclear Co-Repressor 2 (NCOR2) and Phosphodiesterase 4B (PDE4B) were selected based upon predicted targeting by miR-34a (with NCOR2 and PDE4B both targeted by miR-184) and published relevance to psychiatric illness. Luciferase assays identified PDE4B as a target of miR-34a and miR-184, while NCOA1 and NCOR2 were targeted by miR-34a and 184, respectively. qPCR analyses were performed to determine whether changes in miRNA levels correlated with mRNA levels of validated targets. NCOA1 showed an inverse correlation with miR-34a in BP, while NCOR2 demonstrated a positive correlation. In sum, this is the first study to demonstrate miRNA changes in AnCg in psychiatric illness and validate miR-34a as differentially expressed in CNS in MDD. These findings support a mechanistic role for miRNAs in the regulation of stress-responsive genes disrupted in psychiatric illness.


BMC Genomics | 2010

Cross-domain neurobiology data integration and exploration.

Weijian Xuan; Manhong Dai; Josh Buckner; Barbara Mirel; Jean Song; Brian D. Athey; Stanley J. Watson; Fan Meng

BackgroundUnderstanding the biomedical implications of data from high throughput experiments requires solutions for effective cross-scale and cross-domain data exploration. However, existing solutions do not provide sufficient support for linking molecular level data to neuroanatomical structures, which is critical for understanding high level neurobiological functions.ResultsOur work integrates molecular level data with high level biological functions and we present results using anatomical structure as a scaffold. Our solution also allows the sharing of intermediate data exploration results with other web applications, greatly increasing the power of cross-domain data exploration and mining.ConclusionsThe Flex-based PubAnatomy web application we developed enables highly interactive visual exploration of literature and experimental data for understanding the relationships between molecular level changes, pathways, brain circuits and pathophysiological processes. The prototype of PubAnatomy is freely accessible at:[http://brainarray.mbni.med.umich.edu/Brainarray/prototype/PubAnatomy]


computational systems bioinformatics | 2007

An active visual search interface for Medline.

Weijian Xuan; Manhong Dai; Barbara Mirel; Justin Wilson; Brian D. Athey; Stanley J. Watson; Fan Meng

Searching the Medline database is almost a daily necessity for many biomedical researchers. However, available Medline search solutions are mainly designed for the quick retrieval of a small set of most relevant documents. Because of this search model, they are not suitable for the large-scale exploration of literature and the underlying biomedical conceptual relationships, which are common tasks in the age of high throughput experimental data analysis and cross-discipline research. We try to develop a new Medline exploration approach by incorporating interactive visualization together with powerful grouping, summary, sorting and active external content retrieval functions. Our solution, PubViz, is based on the FLEX platform designed for interactive web applications and its prototype is publicly available at: http://brainarray.mbni.med.umich.edu/Brainarray/DataMining/PubViz.


international joint conferences on bioinformatics, systems biology and intelligent computing | 2009

Cross-Domain Neurobiology Data Integration and Exploration

Weijian Xuan; Manhong Dai; Buckner Josh; Barbara Mirel; Jean Song; Brian D. Athey; Stanley J. Watson; Fan Meng

Understanding the biomedical implications of data from high throughput experiments requires solutions for effective cross-scale and cross-domain data exploration. Our work integrates molecular level data with high level biological functions using anatomical structure as a scaffold. The Flex-based PubAnatomy web application we developed enables highly interactive visual exploration of literature and experimental data for understanding the relationships between molecular level changes, pathways, brain circuits and pathophysiological processes. PubAnatomy also allows the sharing of intermediate data exploration results with other web applications, greatly increasing the power of cross-domain data exploration and mining. The prototype of PubAnatomy is freely accessible at: http://brainarray.mbni.med.umich.edu/ Brainarray/prototype/PubAnatomy

Collaboration


Dive into the Manhong Dai's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar

Fan Meng

University of Michigan

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Huda Akil

University of Michigan

View shared research outputs
Top Co-Authors

Avatar

Pinglang Wang

Molecular and Behavioral Neuroscience Institute

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Elvis Jakupovic

Molecular and Behavioral Neuroscience Institute

View shared research outputs
Top Co-Authors

Avatar

Jean Song

University of Michigan

View shared research outputs
Researchain Logo
Decentralizing Knowledge