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1.  The COMBREX Project: Design, Methodology, and Initial Results 
Anton, Brian P. | Chang, Yi-Chien | Brown, Peter | Choi, Han-Pil | Faller, Lina L. | Guleria, Jyotsna | Hu, Zhenjun | Klitgord, Niels | Levy-Moonshine, Ami | Maksad, Almaz | Mazumdar, Varun | McGettrick, Mark | Osmani, Lais | Pokrzywa, Revonda | Rachlin, John | Swaminathan, Rajeswari | Allen, Benjamin | Housman, Genevieve | Monahan, Caitlin | Rochussen, Krista | Tao, Kevin | Bhagwat, Ashok S. | Brenner, Steven E. | Columbus, Linda | de Crécy-Lagard, Valérie | Ferguson, Donald | Fomenkov, Alexey | Gadda, Giovanni | Morgan, Richard D. | Osterman, Andrei L. | Rodionov, Dmitry A. | Rodionova, Irina A. | Rudd, Kenneth E. | Söll, Dieter | Spain, James | Xu, Shuang-yong | Bateman, Alex | Blumenthal, Robert M. | Bollinger, J. Martin | Chang, Woo-Suk | Ferrer, Manuel | Friedberg, Iddo | Galperin, Michael Y. | Gobeill, Julien | Haft, Daniel | Hunt, John | Karp, Peter | Klimke, William | Krebs, Carsten | Macelis, Dana | Madupu, Ramana | Martin, Maria J. | Miller, Jeffrey H. | O'Donovan, Claire | Palsson, Bernhard | Ruch, Patrick | Setterdahl, Aaron | Sutton, Granger | Tate, John | Yakunin, Alexander | Tchigvintsev, Dmitri | Plata, Germán | Hu, Jie | Greiner, Russell | Horn, David | Sjölander, Kimmen | Salzberg, Steven L. | Vitkup, Dennis | Letovsky, Stanley | Segrè, Daniel | DeLisi, Charles | Roberts, Richard J. | Steffen, Martin | Kasif, Simon
PLoS Biology  2013;11(8):e1001638.
Experimental data exists for only a vanishingly small fraction of sequenced microbial genes. This community page discusses the progress made by the COMBREX project to address this important issue using both computational and experimental resources.
doi:10.1371/journal.pbio.1001638
PMCID: PMC3754883  PMID: 24013487
2.  VisANT 4.0: Integrative network platform to connect genes, drugs, diseases and therapies 
Nucleic Acids Research  2013;41(Web Server issue):W225-W231.
With the rapid accumulation of our knowledge on diseases, disease-related genes and drug targets, network-based analysis plays an increasingly important role in systems biology, systems pharmacology and translational science. The new release of VisANT aims to provide new functions to facilitate the convenient network analysis of diseases, therapies, genes and drugs. With improved understanding of the mechanisms of complex diseases and drug actions through network analysis, novel drug methods (e.g., drug repositioning, multi-target drug and combination therapy) can be designed. More specifically, the new update includes (i) integrated search and navigation of disease and drug hierarchies; (ii) integrated disease–gene, therapy–drug and drug–target association to aid the network construction and filtering; (iii) annotation of genes/drugs using disease/therapy information; (iv) prediction of associated diseases/therapies for a given set of genes/drugs using enrichment analysis; (v) network transformation to support construction of versatile network of drugs, genes, diseases and therapies; (vi) enhanced user interface using docking windows to allow easy customization of node and edge properties with build-in legend node to distinguish different node type. VisANT is freely available at: http://visant.bu.edu.
doi:10.1093/nar/gkt401
PMCID: PMC3692070  PMID: 23716640
3.  Thousands of missed genes found in bacterial genomes and their analysis with COMBREX 
Biology Direct  2012;7:37.
Background
The dramatic reduction in the cost of sequencing has allowed many researchers to join in the effort of sequencing and annotating prokaryotic genomes. Annotation methods vary considerably and may fail to identify some genes. Here we draw attention to a large number of likely genes missing from annotations using common tools such as Glimmer and BLAST.
Results
By analyzing 1,474 prokaryotic genome annotations in GenBank, we identify 13,602 likely missed genes that are homologs to non-hypothetical proteins, and 11,792 likely missed genes that are homologs only to hypothetical proteins, yet have supporting evidence of their protein-coding nature from COMBREX, a newly created gene function database. We also estimate the likelihood that each potential missing gene found is a genuine protein-coding gene using COMBREX.
Conclusions
Our analysis of the causes of missed genes suggests that larger annotation centers tend to produce annotations with fewer missed genes than smaller centers, and many of the missed genes are short genes <300 bp. Over 1,000 of the likely missed genes could be associated with phenotype information available in COMBREX. 359 of these genes, found in pathogenic organisms, may be potential targets for pharmaceutical research. The newly identified genes are available on COMBREX’s website.
Reviewers
This article was reviewed by Daniel Haft, Arcady Mushegian, and M. Pilar Francino (nominated by David Ardell).
doi:10.1186/1745-6150-7-37
PMCID: PMC3534567  PMID: 23111013
4.  Deep Sequencing of the Oral Microbiome Reveals Signatures of Periodontal Disease 
PLoS ONE  2012;7(6):e37919.
The oral microbiome, the complex ecosystem of microbes inhabiting the human mouth, harbors several thousands of bacterial types. The proliferation of pathogenic bacteria within the mouth gives rise to periodontitis, an inflammatory disease known to also constitute a risk factor for cardiovascular disease. While much is known about individual species associated with pathogenesis, the system-level mechanisms underlying the transition from health to disease are still poorly understood. Through the sequencing of the 16S rRNA gene and of whole community DNA we provide a glimpse at the global genetic, metabolic, and ecological changes associated with periodontitis in 15 subgingival plaque samples, four from each of two periodontitis patients, and the remaining samples from three healthy individuals. We also demonstrate the power of whole-metagenome sequencing approaches in characterizing the genomes of key players in the oral microbiome, including an unculturable TM7 organism. We reveal the disease microbiome to be enriched in virulence factors, and adapted to a parasitic lifestyle that takes advantage of the disrupted host homeostasis. Furthermore, diseased samples share a common structure that was not found in completely healthy samples, suggesting that the disease state may occupy a narrow region within the space of possible configurations of the oral microbiome. Our pilot study demonstrates the power of high-throughput sequencing as a tool for understanding the role of the oral microbiome in periodontal disease. Despite a modest level of sequencing (∼2 lanes Illumina 76 bp PE) and high human DNA contamination (up to ∼90%) we were able to partially reconstruct several oral microbes and to preliminarily characterize some systems-level differences between the healthy and diseased oral microbiomes.
doi:10.1371/journal.pone.0037919
PMCID: PMC3366996  PMID: 22675498
5.  COMBREX: a project to accelerate the functional annotation of prokaryotic genomes 
Nucleic Acids Research  2010;39(Database issue):D11-D14.
COMBREX (http://combrex.bu.edu) is a project to increase the speed of the functional annotation of new bacterial and archaeal genomes. It consists of a database of functional predictions produced by computational biologists and a mechanism for experimental biochemists to bid for the validation of those predictions. Small grants are available to support successful bids.
doi:10.1093/nar/gkq1168
PMCID: PMC3013729  PMID: 21097892
6.  VisANT 3.5: multi-scale network visualization, analysis and inference based on the gene ontology 
Nucleic Acids Research  2009;37(Web Server issue):W115-W121.
Despite its wide usage in biological databases and applications, the role of the gene ontology (GO) in network analysis is usually limited to functional annotation of genes or gene sets with auxiliary information on correlations ignored. Here, we report on new capabilities of VisANT—an integrative software platform for the visualization, mining, analysis and modeling of the biological networks—which extend the application of GO in network visualization, analysis and inference. The new VisANT functions can be classified into three categories. (i) Visualization: a new tree-based browser allows visualization of GO hierarchies. GO terms can be easily dropped into the network to group genes annotated under the term, thereby integrating the hierarchical ontology with the network. This facilitates multi-scale visualization and analysis. (ii) Flexible annotation schema: in addition to conventional methods for annotating network nodes with the most specific functional descriptions available, VisANT also provides functions to annotate genes at any customized level of abstraction. (iii) Finding over-represented GO terms and expression-enriched GO modules: two new algorithms have been implemented as VisANT plugins. One detects over-represented GO annotations in any given sub-network and the other finds the GO categories that are enriched in a specified phenotype or perturbed dataset. Both algorithms take account of network topology (i.e. correlations between genes based on various sources of evidence). VisANT is freely available at http://visant.bu.edu.
doi:10.1093/nar/gkp406
PMCID: PMC2703932  PMID: 19465394

Results 1-6 (6)