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http://www.comp-sys-bio.org/yeastnet/

This is a portal to the consensus yeast metabolic network as reconstructed from the genome sequence and literature. It is a highly annotated metabolic map that is periodically updated by a team of collaborators from various research groups. The first version of this reconstruction was published in Herrgrd, Swainston et al. (2008) A consensus yeast metabolic reconstruction obtained from a community approach to systems biology Nature Biotechnol. 26, 1155-1160 (you can access that network here). A second version has now been released and is awaiting publication. We plan on continuing to update this resource towards a complete metabolic network of yeast. All versions will remain accessible for historical purposes, however it is highly recommended that you always use the latest one since that is the most up to date. This effort started on the shoulders of a number of reconstructions of the metabolic network of yeast based on genomic and literature data that were published separately. (iMM904 and iLL672) However, due to the different approaches utilized in them, those earlier reconstructions had a significant number of differences. In addition they suffered from the use of non-standard names and overall they were not annotated with methods that are machine-readable. A community effort in 2007, led by the Manchester Centre for Integrative Systems Biology and the YSBN resulted in a consensus network representation of yeast metabolism, reconciling the earlier results. That effort is now ongoing under the leadership of the MCISB and with collaboration with colleagues under the UNICELLSYS FP7 project. Availability The network reconstruction is primarily assembled and provided as an SBML file enriched with MIRIAM-compliant annotations (which are embedded in the SBML through RDF). All small and macro- molecules are referenced to an authoritative database (e.g. Uniprot, ChEBI, etc.). All molecules and reactions are also annotated with appropriate publications that contain supporting evidence. Thus this network is entirely traceable and is presented in a computational framework. SBML is a format that is understood by a large number of software applications (see sbml.org). While the SBML file is the most efficient computational resource for these data, casual users also need access to the network. That is provided by a searchable relational database accessed directly from this website. The database pages also allow readers to add comments to any chemical species or reaction. Such comments are taken into consideration by the team collating new versions of the network and can lead to corrections and additions to the network. This reconstruction is provided in the following formats: :* an SBML file containing the reaction network and annotations, located to specific sub-cellular compartments :* an SBML file containing the reaction network and annotations without subcellular compartmentation (all reactions happening in a single compartment). :* a searcheable relational database, which uses the B-Net software from Pedro Mendes' group. The database version of this data set is managed with the B-Net software created in Pedro Mendes' group at the Virginia Bioinformatics Institute. B-Net's schema is a detailed representation of the underlying biochemistry and regulation. A number of reconstructions of the metabolic network of yeast based on genomic and literature data have been published. However, due to different approaches utilized in the reconstruction as well as different interpretations of the literature, the earlier reconstructions have significant number of differences. A community effort resulted in a consensus network model of yeast metabolism, combining results from previous models.

Proper citation: Yeast consensus metabolic network - A consensus reconstruction of yeast metabolism (RRID:SCR_002135) Copy   

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https://scicrunch.org/resolver/SCR_002250

THIS RESOURCE IS NO LONGER IN SERVICE. Documented Jul 19, 2024. Metadatabase manually curated that provides web accessible tools related to genomics, transcriptomics, proteomics and metabolomics. Used as informative directory for multi-omic data analysis.

Proper citation: OMICtools (RRID:SCR_002250) Copy   

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http://www.broadinstitute.org/mpg/snap/

A computer program and web-based service for the rapid retrieval of linkage disequilibrium proxy single nucleotide polymorphism (SNP) results given input of one or more query SNPs and based on empirical observations from the International HapMap Project and the 1000 Genomes Project. A series of filters allow users to optionally retrieve results that are limited to specific combinations of genotyping platforms, above specified pairwise r2 thresholds, or up to a maximum distance between query and proxy SNPs. SNAP can also generate linkage disequilibrium plots

Proper citation: SNAP - SNP Annotation and Proxy Search (RRID:SCR_002127) Copy   

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http://www.structuralgenomics.org/

The Structural Genomics Project aims at determination of the 3D structure of all proteins. It also aims to reduce the cost and time required to determine three-dimensional protein structures. It supports selection, registration, and tracking of protein families and representative targets. This aim can be achieved in four steps : -Organize known protein sequences into families. -Select family representatives as targets. -Solve the 3D structure of targets by X-ray crystallography or NMR spectroscopy. -Build models for other proteins by homology to solved 3D structures. PSI has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm. The project has been organized into two separate phases. The first phase was dedicated to demonstrating the feasibility of high-throughput structure determination, solving unique protein structures, and preparing for a subsequent production phase. The second phase, PSI-2, has focused on implementing the high-throughput structure determination methods developed in PSI-1, as well as homology modeling and addressing bottlenecks like modeling membrane proteins. The first phase of the Protein Structure Initiative (PSI-1) saw the establishment of nine pilot centers focusing on structural genomics studies of a range of organisms, including Arabidopsis thaliana, Caenorhabditis elegans and Mycobacterium tuberculosis. During this five-year period over 1,100 protein structures were determined, over 700 of which were classified as unique due to their < 30% sequence similarity with other known protein structures. The primary goal of PSI-1 was to develop methods to streamline the structure determination process, resulted in an array of technical advances. Several methods developed during PSI-1 enhanced expression of recombinant proteins in systems like Escherichia coli, Pichia pastoris and insect cell lines. New streamlined approaches to cell cloning, expression and protein purification were also introduced, in which robotics and software platforms were integrated into the protein production pipeline to minimize required manpower, increase speed, and lower costs. The goal of the second phase of the Protein Structure Initiative (PSI-2) is to use methods introduced in PSI-1 to determine a large number of proteins and continue development in streamlining the structural genomics pipeline. Currently, the third phase of the PSI is being developed and will be called PSI: Biology. The consortia will propose work on substantial biological problems that can benefit from the determination of many protein structures Sponsors: PSI is funded by the U.S. National Institute of General Medical Sciences (NIGMS),

Proper citation: Protein Structure Initiative (RRID:SCR_002161) Copy   

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https://cran.r-project.org/web/packages/LDheatmap/index.html

Software application that plots measures of pairwise linkage disequilibria for SNPs (entry from Genetic Analysis Software)

Proper citation: LDHEATMAP (RRID:SCR_006312) Copy   

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http://www.gepas.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. An integrated packages of tools for microarray data analysis. GEPAS provides a web-based interface that offers diverse analysis options from the early step of preprocessing (normalization of Affymetrix and two-color microarray experiments and other preprocessing options), to the final step of the functional profiling of the experiment (using Gene Ontology, pathways, PubMed abstracts etc.), which include different possibilities for clustering, gene selection, class prediction and array-comparative genomic hybridization management.

Proper citation: Gene Expression Profile Analysis Suite (RRID:SCR_008341) Copy   

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http://wpicr.wpic.pitt.edu/WPICCompGen/hclust/hclust.htm

Software application that is a simple clustering method that can be used to rapidly identify a set of tag SNP's based upon genotype data (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: HCLUST (RRID:SCR_009154) Copy   

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http://soap.genomics.org.cn/

Software package that provides full solution to next generation sequencing data analysis consisting of an alignment tool (SOAPaligner/soap2), a re-sequencing consensus sequence builder (SOAPsnp), an indel finder ( SOAPindel ), a structural variation scanner ( SOAPsv ), a de novo short reads assembler ( SOAPdenovo ), and a GPU-accelerated alignment tool for aligning short reads with a reference sequence. (SOAP3/GPU)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SOAP (RRID:SCR_000689) Copy   

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https://sbpdiscovery.org/research/centers/conrad-prebys-center-for-chemical-genomics/

The Conrad Prebys Center for Chemical Genomics (CPCCG) uses advanced screening technologies to identify high level chemical probes that interact with proteins involved in cellular processes. Optimization of these probes using medicinal chemistry and informatics will form the basis of a new generation of medicines. CPCCG is 1 of 4 Comprehensive Centers chosen nationally to be a part of the Molecular Libraries Probe Program (MLP), which established the Molecular Libraries Probe Production Centers Network (MLPCN). The goal is to produce small molecule probes that allow research into health and disease on the cellular level. CPCCG core services span a range of biochemical and cell-based screens for obtaining hits and provide chemistry resources for optimizing hits into probes or drug development. - Full scale screening capabilities and technology which can provide rapid screening on a broad diversity of assays and detection platforms - Several fully-integrated industrial-scale high-throughput screening (HTS) workstations - HTS microscopy/HCS and novel algorithm development for image analysis - Full hit-to-probe chemistry and exploratory pharmacology - Powerful NMR based Chemical Fragment Screening - Highly integrated informatics infrastructure and efficient data mining capabilities - Protein production facility - Cell production facility for scale-up tissue culture The CPCCG Screening Core can screen 96, 384 or 1536 well formats using either biochemical or cell-based assays, and can process over 300,000 wells per day. Total throughput capacity will climb to over 2 million compounds per day following the opening of Burnhams east coast campus in Lake Nona, Florida.

Proper citation: Conrad Prebys Center for Chemical Genomics (RRID:SCR_001687) Copy   

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http://www.softberry.com/

Developer of software tools for genomic research focused on computational methods of high throughput biomedical data analysis, including software to support next generation sequencing technologies, transcriptome analysis with RNASeq data, SNP detection and selection of disease specific SNP subsets. Provides custom genome annotation services.

Proper citation: SoftBerry (RRID:SCR_000902) Copy   

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http://hanalyzer.sourceforge.net/

An open-source data integration system designed to assist biologists in explaining the results observed in genome-scale experiments as well as generating new hypotheses. It combines information extraction techniques, semantic data integration, and reasoning and facilitates network visualization. The Hanalyzer source code and binaries are available for download.

Proper citation: Hanalyzer (RRID:SCR_000923) Copy   

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https://www.hsph.harvard.edu/alkes-price/software/

Software application that uses genotyping data from SNP arrays for accurately inferring chromosomal segments of distinct continental ancestry in admixed populations, using dense genetic data. (entry from Genetic Analysis Software)

Proper citation: Hapmix (RRID:SCR_004203) Copy   

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http://sonorus.princeton.edu/hefalmp/

HEFalMp (Human Experimental/FunctionAL MaPper) is a tool developed by Curtis Huttenhower in Olga Troyanskaya's lab at Princeton University. It was created to allow interactive exploration of functional maps. Functional mapping analyzes portions of these networks related to user-specified groups of genes and biological processes and displays the results as probabilities (for individual genes), functional association p-values (for groups of genes), or graphically (as an interaction network). HEFalMp contains information from roughly 15,000 microarray conditions, over 15,000 publications on genetic and physical protein interactions, and several types of DNA and protein sequence analyses and allows the exploration of over 200 H. sapiens process-specific functional relationship networks, including a global, process-independent network capturing the most general functional relationships. Looking to download functional maps? Keep an eye on the bottom of each page of results: every functional map of any kind is generated with a Download link at the bottom right. Most functional maps are provided as tab-delimited text to simplify downstream processing; graphical interaction networks are provided as Support Vector Graphics files, which can be viewed using the Adobe Viewer, any recent version of Firefox, or the excellent open source Inkscape tool.

Proper citation: Human Experimental/FunctionAL MaPper: Providing Functional Maps of the Human Genome (RRID:SCR_003506) Copy   

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http://gfpweb.aecom.yu.edu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 12,2023. Database of expression patterns of C. elegans promoter::GFP constructs. A text description of the observed pattern is provided, indicating the stage(s) and tissue(s) in which GFP is expressed. Also available for some strains are the corresponding 2D and 3D images. Investigators may browse the entire list, search by gene name, tissue, stage, and pattern. Search results may be downloaded in .csv and .txt formats. All of the strains in the expression pattern database are displayed in the browse page. The records are organized by gene; information such as locus name, genomic location (WormBase), the presence of images and videos, and the actual expression pattern are shown in a tabular format.

Proper citation: Expression Patterns for C. elegans promoter GFP fusions (RRID:SCR_001619) Copy   

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http://www.mknt.hu/sites/default/files/NEPSYBANK_0.doc

The Hungarian Society of Clinical Neurgenetics established a nationwide collaboration for prospective collection of human biological materials and databases from patient with neurological and psychiatric diseases. The basic triangle of the NEPSYBANK is the sample, the information and the study management. The present participants of the NEPSYBANK are the Department of Neurology and Psychiatry of the four Medical Universities (in Budapest, Debrecen, Pecs, Szeged) and the National Institute of Psychiatry and Neurology in Budapest. The NEPSYBANK is a disease based biobank collecting both phenotypical and environmental data and biological materials such as DNA/RNA, whole blood, plasma, cerebral spinal fluid, muscle / nerve / skin biopsy, brain, and fibroblast. The target of the diseases is presently (Phase I): stroke syndromes, dementias, movement disorders, motoneuron diseases, epilepsy, multiple sclerosis, schizophrenia, alcohol addiction. In the near future (Phase II.) it is planned to enlarge the scale with headaches, disorders of the peripheral nerves, disorders of neuromuscular transmission, disorders of skeletal muscle, depression, anxiety. DNA/RNA is usually extracted from whole blood, but occasionally different tissues such as muscle, brain etc. can be used as well. The extracting procedures differ among the institutes, but in all cases the concentration and the quality of the DNA/RNA must be registered in the database. Participating institutional biobanks have committed themselves to follow common quality standards, which provide access to samples after prioritization on scientific grounds only. In every case the following data are registered. 1. General data: main bank categories, age, sex, ethnicity, body height, body weight, economic stats, education, type of place of living, marital status, birth complications, alcohol, drugs, smoking. 2. Sample properties (sample ID, type of sample, date of extraction, concentration, and level of purity). General patient data as blood pressure, heart rate, internal medical status, ECG, additional diseases. Disease specific question e.g. in schizophrenia the diagnosis after DSMIV and ICD 10, detailed diagnostic questions after both classification, detailed psychiatric and neurological status, laboratory findings, rating scales, data of neuroimaging, genetic tests, applied medication (with generic name, dose, duration), adverse drug effects and other treatments. The Biobank Information Management System (BIMS) is responsible for linkage of databases containing information on the individual sample donors. If you want to have samples from the NEPSYBANK an application must be submitted containing the following information: short research plan including aims and study design, ethic application with a positive decision, specific demands regarding the right of disposition, agreements with grant organizations which regulate immaterial property, information about financing (academic grants, support from industry). All participants have the right to withdraw their samples through a simple order.

Proper citation: Hungarian Neurological-Psychiatric Biobank (RRID:SCR_003715) Copy   

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http://www.broadinstitute.org/cancer/cga/oncotator

A tool for annotating human genomic point mutations and indels with data relevant to cancer researchers. Genomic Annotations, Protein Annotations, and Cancer Annotations are aggregated from many resources. A standalone version of Oncotator is being developed.

Proper citation: Oncotator (RRID:SCR_005183) Copy   

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http://www.sugp.caltech.edu/SpBase/

SpBase is designed to present the results of the genome sequencing project for the purple sea urchin. The sequences and annotations emerging from this effort are organized in a database that provides the research community access to those data not normally presented through National Center for Biotechnology Information and other large databases. Additionally, the unique information on that links gene identities and sequences to the plate and well location to the library filters from the Sea Urchin genome Resource will also be presented. The software used to organize and present the sea urchin genome comes from GMOD, a collection of open source software tools for creating and managing genome-scale biological databases. That sea urchins eggs and embryos have long remained a popular research subject for cell and developmental biologists is one rationale for sequencing the genome. In addition, studies of embryonic development in the California Purple Sea Urchin, Strongylocentrotus purpuratus , have paralleled the emergence of molecular techniques ranging from the characterization of genomic repeat sequences in the 1970''s to the elucidation of gene regulatory networks in recent times. The parent of this site, SUGP, was meant to provide a focal point for the exchange of genomic information as the genome of the Purple sea urchin was being sequenced. Over these past years it has served as a repository for small sequencing projects and a source of sequence information useful for gene discovery projects. Here one could find information on macro-array libraries of cDNAs from the purple sea urchin and genomic DNA from several species. In addition, a Sequence Tag Connector (STC) collection has been assembled from 5% of the genome sequence and a very extensive repeat sequence catalog prepared. All of the sequence data that we maintained at SUGP was incorporated into the new SPBase. Of course, it is all in public sequence databases such as the National Center for Biological Information as well. Some additional sequence information is available at the Resource Center of the German Human Genome Project. With the publication of The Genome of the Sea Urchin Strongylocentrotus purpuratus by The Sea Urchin Genome Sequencing Consortium a link to the first 9941 gene annotations are now publicly available. The effort to sequence the whole purple sea urchin genome was a cooperative one that included contributions from the Sea Urchin Genome Facility here at the Center for Computational Regulatory Genomics, Beckman Institute, Caltech, and support from the Human Genome Research Institute of the National Institutes of Health. The sequencing was done at the Baylor College of Medicine, Human Genome Sequencing Center, Houston, Texas. Funding was approved based on an initiative submitted by the Sea Urchin Genome Advisory Committee.

Proper citation: SpBase - Strongylocentrotus purpuratus: the Sea Urchin Genome Database (RRID:SCR_007441) Copy   

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http://wavi.bioinfo.cnio.es/

A versatile web-server application for the analysis and visualization of array-CGH data.

Proper citation: waviCGH (RRID:SCR_006662) Copy   

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http://probeexplorer.cicancer.org/principal.php

Probe Explorer is an open access web-based bioinformatics application designed to show the association between microarray oligonucleotide probes and transcripts in the genomic context, but flexible enough to serve as a simplified genome and transcriptome browser. Coordinates and sequences of the genomic entities (loci, exons, transcripts), including vector graphics outputs, are provided for fifteen metazoa organisms and two yeasts. Alignment tools are used to built the associations between Affymetrix microarrays probe sequences and the transcriptomes (for human, mouse, rat and yeasts). Search by keywords is available and user searches and alignments on the genomes can also be done using any DNA or protein sequence query. Platform: Online tool

Proper citation: ProbeExplorer (RRID:SCR_007116) Copy   

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http://www.sanger.ac.uk/science/tools/seqtools

Software for sequence alignments that displays multiple match sequences aligned against a single genomic reference sequence. It can be used for manipulation, display and annotation of genomic data, to check the quality of an alignment, to find missing/misaligned sequence, and to identify splice sites and polyA sites.

Proper citation: Blixem (RRID:SCR_015994) Copy   

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