Biological Concept Diagram Editor (BCDE) is a tool designed for efficient knowledge and data capture from electronic resources for sharing, mining and presentation purposes. Besides standard diagramming functions, it has powerful data capture and annotation capabilities. BCDE is compatible with BioPAX and it also exports to Powerpoint and Visio. http://portal.ncibi.org/gateway/bcde.html BCDE molecular interactions, bioinformatics tools, workflows, Diagram Editor ncibi-help@umich.edu University of Michigan Alpha Fan Meng NCIBI ncibi-help@umich.edu A common task in many modern bioinformatics applications is to match a set of nucleotide query sequences against a large sequence dataset. Exis-ting tools, such as BLAST, are designed to evaluate a single query at a time and can be unacceptably slow when the number of sequences in the query set is large. In this paper, we present a new algorithm, called miBLAST, that evaluates such batch workloads efficiently. At the core, miBLAST employs a q-gram filtering and an index join for efficiently detecting similarity between the query sequences and database sequences. This set-oriented technique, which indexes both the query and the database sets, results in substantial performance improvements over existing methods. Our results show that miBLAST is significantly faster than BLAST in many cases. For example,! miBLAST aligned 247 965 oligonucleotide sequences in the Affymetrix probe set against the Human UniGene in 1.26 days, compared with 27.27 days with BLAST (an improvement by a factor of 22). The relative performance of miBLAST increases for larger word sizes; however, it decreases for longer queries. miBLAST employs the familiar BLAST statistical model and output format, guaranteeing the same accuracy as BLAST and facilitating a seamless transition for existing BLAST users. miBLAST microarray, BLAST NCIBI Jignesh Patel University of Michigan Educational Community License (free for all uses) 1.0 2005-08-01 http://www.eecs.umich.edu/miblast/ SAGA stands for Subgraph Index for Approximate Graph Alignment. It is an efficient tool for approximate subgraph matching. SAGA allows users to match a query graph against a large database of graphs. At the core of SAGA is a flexible graph distance model that incorporates node approximate matching as well as approximate structure matching. A powerful indexing method is implemented to speed up the matching process. Some applications of SAGA include querying/comparing pathways and querying parsed biomedical literature databases to find similar documents. Glenn Tarcea http://portal.ncibi.org/gateway/saga.html SAGA NCIBI University of Michigan ncibi-help@umich.edu http://marimba.hegroup.org// Peter Woolf microarray, information refining, bioinformatics tools ncibi-help@umich.edu University of Michigan Marimba is a web based static Bayesian network analysis tool designed for analyzing and interpreting gene expression data. Marimba NCIBI University of Michigan PEBL is a Python library and application for learning Bayesian networkstructure from data and prior knowledge that provides featuresunmatched by alternative software packages: the ability to useinterventional data, flexible specification of structural priors,modeling with hidden variables and exploitation of parallelprocessing. Abhik Shah PEBL NCIBI http://pebl-project.googlecode.com/ ncibi-help@umich.edu ncibi-help@umich.edu 07n interactive database, document summarization, natural language processing, journal articles Alex Ade NCIBI University of Michigan PubMed Database SQL database with all PubMed baseline and update records, sentence-segmented and named entity tagged for genes, proteins, and MeSH terms. Contains over 17 million citations from Medline and other life sciences journals. Updated nightly. The Web-based GeneChip Analysis System (WGAS) incorporates popular probe-, gene- and function category-level analysis methods through straightforward web interface. It natively supports custom GeneChip probe set definition files for more accurate data interpretation. Users can also access to any Cel files deposited in NCBI GEO database for re-analysis and comparison. WGAS University of Michigan Manhong Dai NCIBI data management, microarray, gene expression regulation, snp, collaboration, file sharing ncibi-help@umich.edu http://arrayanalysis.mbni.med.umich.edu/arrayanalysis.html Peter Woolf University of Michigan ncibi-help@umich.edu miniTUBA 0.9 NCIBI http://portal.ncibi.org/gateway/minituba.html miniTUBA is a dynamic Bayesian network analysis tool designed for analyzing and interpreting molecular clinical data. information refining, gene expression regulation, bioinformatics tools A web database with the goal of integrating SNP function annotation all public sources as well as those derived from various sequence/structure analysis programs. A powerful SNP search function, utilizing genomic and HapMap II data, provides the capability of finding any structurally and genetically SNPs. Fan Meng SNP Function Portal 0.2 University of Michigan NCIBI http://brainarray.mbni.med.umich.edu/Brainarray/Database/SearchSNP/snpfunc.aspx data management, interactive database, document summarization, genomic sequence analysis, bioinformatics tools, snp, function, genome-wide scanning, hapmap ncibi-help@umich.edu NCIBI lennart.martens@ebi.ac.uk, pride-support@ebi.ac.uk Centralized standards compliant public data repository for proteomics data, protein and peptide identifications with experimental annotations. free, but registration required EBI Lennart Martens Proteins, peptides, mass spectrometry, annotations, standards Protein Identifications database http://www.ebi.ac.uk/pride Proteomics, mass spectrometry, peptides, Ensembl, PeptideProphet, uniform re-analysis of raw data NCIBI Institute for Systems Biology http://www.peptideatlas.org free, but registration required Peptide Atlas edeutsch@systemsbiology.org Multi-organism, publicly accessible compendium of peptides identified in a large set of tandem mass spectrometry proteomics experiments, some published, many still unpublished. All results of sequence searching are processed through PeptideProphet to derive a probability of correct identification for all results in a uniform manner ensuring a high quality database. All peptides are mapped to Ensembl and can be viewed as custom tracks on the Ensembl genome browser. Eric Deutsch Mass spectrometry, proteins, peptides, file sharing, security, public Mark Gjukich, Philip Andrews Free and open source filesharing tool that enables collections of computers to easily share and cite scientific data sets in a secure and scalable fashion. More than 5200 data sets on line as of mid-2008. Tranche is the filesharing link between PRIDE and Peptide Atlas for the Human Proteome Organization (HUPO) Plasma Proteome Project via ProteomExchange. NCIBI Tranche Project http://tranche.proteomecommons.org free, but registration required markgj@umich.edu, andrewsp@umich.edu University of Michigan A web based visual corpus summarization system for biomedical literature. University of Michigan BioSearch-2D http://portal.ncibi.org/gateway/biosearch2d.html NCIBI ncibi-help@umich.edu data management, interactive database, information refining, document summarization, natural language processing, keyword search, bioinformatics tools Vasudeva Mahavisno http://murphylab.web.cmu.edu/services/SLIF/ Carnegie Mellon SLIF SLIF finds fluorescence microscope images in on-line journal articles, and indexes them according to cell line, proteins visualized, and resolution. Dr. Robert F. Murphy NCIBI ncibi-help@umich.edu A resource for examining gene expression in cancer. The goal of the project is to collect, standardize, analyze, and deliver published cancer gene expression data to the research community. Probe the expression of a gene across thousands of cancer samples or explore genes, processes, and pathways deregulated in a particular type of cancer. Oncomine pre-computes cancer profiles, clusters, and gene set modules so you can focus on discovery. http://www.oncomine.org/main/index.jsp microarray, cancer, gene expression regulation, function, genome-wide scanning ncibi-help@umich.edu NCIBI Oncomine Compendia Bioscience Oncomine Team 3.0 interactive database, document summarization, natural language processing, journal articles Alex Ade NCIBI SQL database with all open access articles from PubMed Central, sentence-segmented, citation network extracted, and named entity tagged for genes, proteins, and UMLS concepts. Updated monthly. University of Michigan PMCOA Database ncibi-help@umich.edu Custom CDF University of Michigan Manhong Dai NCIBI ncibi-help@umich.edu 7.0 2006-05-01 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. http://brainarray.mbni.med.umich.edu/Brainarray/Database/CustomCDF/genomic_curated_CDF.asp interactive database, information refining, natural language processing, keyword search, bioinformatics tools, journal articles, open source An interface to the NCBI Entrez systems that ranks query output based on the likelihood that you will click on an entry. Ranking is performed by building up a profile based on past user behavior. Multiple profiles per user can be defined. University of Michigan http://portal.ncibi.org/gateway/misearch.html MiSearch Zach Wright ncibi-help@umich.edu NCIBI We introduce a stochastic graph-based method for computing relative importance of textual units for Natural Language Processing. We test the technique on the problem of Text Summarization (TS). Extractive TS relies on the concept of sentence salience to identify the most important sentences in a document or set of documents. Salience is typically defined in terms of the presence of particular important words or in terms of similarity to a centroid pseudo-sentence. We consider a new approach, LexRank, for computing sentence importance based on the concept of eigenvector centrality in a graph representation of sentences. In this model, a connectivity matrix based on intra-sentence cosine similarity is used as the adjacency matrix of the graph representation of sentences. Our system, based on LexRank ranked in first place in more than one task in the recent DUC 2004 evaluation. In this paper we present a detailed analysis of ou! r approach and apply it to a larger data set including data from earlier DUC evaluations. We discuss several methods to compute centrality using the similarity graph. The results show that degree-based methods (including LexRank) outperform both centroid-based methods and other systems participating in DUC in most of the cases. Furthermore, the LexRank with threshold method outperforms the other degree-based techniques including continuous LexRank. We also show that our approach is quite insensitive to the noise in the data that may result from an imperfect topical clustering of documents. NCIBI LexRank Demo ncibi-help@umich.edu Dragomir Radev University of Michigan Alpha document summarization, natural language processing http://tangra.si.umich.edu/~radev/lexrank/ GIN-IE: Gene Interaction Extraction from the Literature http://gin.ncibi.org/rss/gin-ie/interactions.rss NCIBI Dragomir Radev Besides the fact that there is a relationship between a pair of molecules, the context information such as the type and the directionality are also important. To extract the relationships and their types and directionalities we use the sentences, and their syntactic and dependency parse tree structures, which enables us to make syntax-aware inferences about the roles of the entities in a sentence. We investigate both machine learning based approaches and rule-based approaches. While machine learning based approaches achieve more balanced precision-recall performances, rule-based methods achieve higher precision in the expense of recall. High precision is an important requirement for most real-life applications. The high precision interaction extraction pipeline is integrated with the daily processing of the Pubmed updates pipeline. The extracted interactions are published as an RSS feed and included into the NCIBI data repository. ncibi-help@umich.edu University of Michigan Natural Language Processing, Text Mining, Information Extraction ncibi-help@umich.edu Cytoscape data management, microarray, information refining, natural language processing, molecular interactions, gene expression regulation, network visualization, open source UCSD Cytoscape Team Cytoscape is an open source bioinformatics software platform for visualizing molecular interaction networks and integrating these interactions with gene expression profiles and other state data. http://www.cytoscape.org/ Institute for Systems Biology http://murphylab.web.cmu.edu/services/PSLID/ ncibi-help@umich.edu Carnegie Mellon PSLID PSLID provides a structured, well-annotated database of fluorescence microscope images depicting subcellular location proteins. Two interfaces are currently provided: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. Dr. Robert F. Murphy NCIBI release 2008-08-12 3.0.1 protein interaction, network visualization, XQuery, interactive database, information refining, molecular interactions, bioinformatics tools, ncibi-help@umich.edu Cytoscape Plugin for MiMI Jing Gao NCIBI http://portal.ncibi.org/gateway/mimiplugin.html Available University of Michigan This plugin retrieves and displays molecular interactions from Michigan Molecular Interactions (MiMI) database. Using this plugin, users can extend and edit current networks interactively, link out interactions to external web resources, edit interaction annotations and use cerebral layout. By integrating with NCIBI BioNlp and SAGA, users can get literature information associated with interactions and conduct graphic match against biological pathways. Yes Java, Cytoscape Java http://portal.ncibi.org/gateway/mimi.html ncibi-help@umich.edu University of Michigan 3.1 Release Yes Limited MiMI Free for Non-commercial Use Glenn Tarcea Terry Weymouth protein interaction, XQuery, molecular interactions, Pathway, keyword search Yes NCIBI MiMI is an XML based molecular interactions database and front end. MiMI supports XQuery, Keyword, Forms based and CLI access. http://portal.ncibi.org/gateway/gene2mesh.html Alex Ade NCIBI ncibi-help@umich.edu University of Michigan Gene2MeSH is an automated annotation tool that associates Medical Subject Heading (MeSH) terms with genes using the National Library of Medicine's PubMed literature database. Gene2Mesh Java, Cytoscape 0.8 March 13, 2009 beta http://metabplugin.ncibi.org/ Jing Gao MetScape is a Cytoscape plugin which is used to visualize and analyze metabolomic data. It uses the data from Edinburgh Human Metabolic Network reconstruction. It allows user to visualize compound networks and display related information about reactions, enzymes, and pathways. NCIBI Compound network, pathway network, network visualization, network layout, information refining ncibi-help@umich.edu University of Michigan MetScape mass spectroscopy, proteomics NCIBI X! Tandem open source is software that can match tandem mass spectra with peptide sequences, in a process that has come to be known as protein identification. This software has a very simple, sophisticated application programming interface (API): it simply takes an XML file of instructions on its command line, and outputs the results into an XML file, which has been specified in the input XML file. Global Proteome Machine Organization Ron Beavis ncibi-help@umich.edu http://www.thegpm.org/TANDEM/ X!Tandem http://www.broad.mit.edu/cancer/software/genepattern/index.html gp-help@broad.mit.edu NCIBI Genepattern Team GenePattern 2007-05-01 3.0 Broad Institute GenePattern is a powerful analysis workflow tool developed to support multidisciplinary genomic research programs and designed to encourage rapid integration of new techniques. workflow, anaysis pipeline perl natural language processing University of Michigan http://www.clairlib.org clair library for natural language processing, information retrieval, and network analysis ncibi-help@umich.edu ClairLib NCIBI Dragomir Radev http://portal.ncibi.org/gateway/mead.html MEAD is a publicly available toolkit for multi-lingual summarization and evaluation. The toolkit implements multiple summarization algorithms (at arbitrary compression rates) such as position-based, Centroid[RJB00], TF*IDF, and query-based methods. Methods for evaluating the quality of the summaries include co-selection (precision/recall, kappa, and relative utility) and content-based measures (cosine, word overlap, bigram overlap). NCIBI document summarization, natural language processing University of Michigan Public Domain MEAD Dragomir Radev ncibi-help@umich.edu GIN-NA is a system for analysing molecule interaction networks. The interaction networks are retrieved from the MiMI database, which integrates protein interactions from diverse biological data sources. Analysis of two types of networks are performed, namely molecule-specific networks and disease-specific networks. Molecule-specific networks are the networks of interactions in the neighborhood of a molecule. Besides the general network statistics such as average degree, power-law degree distribution, clustering coefficient, and shortest path statistics, GIN-NA ranks the molecules in the network based on graph centrality measures and second neighbor statistics. Disease-specific networks are built by compiling lists of known disease genes and retrieving the interactions among these genes and their neighborhood. We hypothesize that the genes central in the disease-specific gene interaction network are likely to be related to the disease and rank the genes based on their centrality scores. Currently, GIN-NA provides disease-specific networks for the four Driving Biological Problems, Prostate Cancer, Type 1 Diabetes, Type 2 Diabetes, and Bipolar Disorder. ncibi-help@umich.edu http://gin.ncibi.org/ GIN-NA: Gene Interaction Network Analysis Dragomir Radev interaction network analysis, network centrality, gene-disease associations NCIBI University of Michigan ncibi-help@umich.edu natural language processing, bioinformatics tools, snp http://brainarray.mbni.med.umich.edu/Brainarray/DataMining/MarkerInfoFinder/default.aspx University of Michigan MarkerInfoFinder MarkerInfoFinder is a web-based Medline abstract search engine that supports the use of genetic marker IDs and flexible positional/linkage disequilibrium criteria. Manhong Dai NCIBI