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http://www.stanford.edu/group/nusselab/cgi-bin/wnt/

A resource for members of the Wnt community, providing information on progress in the field, maps on signaling pathways, and methods. The page on reagents lists many resources generously made available to and by the Wnt community. Wnt signaling is discussed in many reviews and in a recent book. There are usually several Wnt meetings per year.

Proper citation: Wnt homepage (RRID:SCR_000662) Copy   

•   Source: SciCrunch Registry

http://gowiki.tamu.edu/wiki/

A wiki where users of the Gene Ontology can contribute and view notes about how specific GO terms are used. GONUTS can also be used as a GO term browser, or to search for GO annotations of specific genes from included organisms. The rationale for this wiki is based on helping new users of the gene ontology understand and use it. The GONUTS wiki is not an official product of the the Gene Ontology consortium. The GO consortium has a public wiki at their website, http://wiki.geneontology.org/. Maintaining the ontology involves many decisions to carefully choose terms and relationships. These decisions are currently made at GO meetings and via online discussion using the GO mailing lists and the Sourceforge curator request tracker. However, it is difficult for someone starting to use GO to understand these decisions. Some insight can be obtained by mining the tracker, the listservs and the minutes of GO meetings, but this is difficult, as these discussions are often dispersed and sometimes don't contain the GO accessions in the relevant messages. Wikis provide a way to create collaboratively written documentation for each GO term to explain how it should be used, how to satisfy the true path requirement, and whether an annotation should be placed at a different level. In addition, the wiki pages provide a discussion space, where users can post questions and discuss possible changes to the ontology. GONUTS is currently set up so anyone can view or search, but only registered users can edit or add pages. Currently registered users can create new users, and we are working to add at least one registered user for each participating database (So far we have registered users at EcoliHub, EcoCyc, GOA, BeeBase, SGD, dictyBase, FlyBase, WormBase, TAIR, Rat Genome Database, ZFIN, MGI, UCL and AgBase...

Proper citation: GONUTS (RRID:SCR_000653) Copy   

•   Source: SciCrunch Registry

http://www.bumc.bu.edu/cardiovascularproteomics/

The Cardiovascular Proteomics Center is a research center funded by the NIH/NHLBI to analyze and identify proteins that may be modified or created by oxidative stress. The CPC is developing and applying new proteomics methodology and instrumentation to the analysis of known proteins and those yet to be discovered.

Proper citation: Cardiovascular Proteomics Center (RRID:SCR_000603) Copy   

•   Source: SciCrunch Registry

http://www.rostlab.org/cms/

A lab organization which has bases in Munich, Germany and at Columbia University and focuses its research on protein structure and function using sequence and evolutionary information. They utilize machine learning and statistical methods to analyze genetic material and its gene products. Research goals of the lab involve using protein and DNA sequences along with evolutionary information to predict aspects of the proteins relevant to the advance of biomedical research.

Proper citation: ROSTLAB (RRID:SCR_000792) Copy   

•   Source: SciCrunch Registry

https://www.athensresearch.com/

Commercial supplier of bioproducts for studies of inflammation, autoimmune disease, cancer, coronary disease, Alzheimer's Disease and more. These include antibodies, enzymes, coagulation factors, and assay kits.

Proper citation: Athens Research and Technology (RRID:SCR_001079) Copy   

•   Source: SciCrunch Registry

http://www.genome.jp/kegg/expression/

Database for mapping gene expression profiles to pathways and genomes. Repository of microarray gene expression profile data for Synechocystis PCC6803 (syn), Bacillus subtilis (bsu), Escherichia coli W3110 (ecj), Anabaena PCC7120 (ana), and other species contributed by the Japanese research community.

Proper citation: Kyoto Encyclopedia of Genes and Genomes Expression Database (RRID:SCR_001120) Copy   

•   Source: SciCrunch Registry

https://medicine.yale.edu/keck/nida/yped/

Open source system for storage, retrieval, and integrated analysis of large amounts of data from high throughput proteomic technologies. YPED currently handles LCMS, MudPIT, ICAT, iTRAQ, SILAC, 2D Gel and DIGE. The repository contains data sets which have been released for public viewing and downloading by the responsible Primary Investigators. It includes proteomic data generated by the Yale NIDA Neuroproteomics Center (http://medicine.yale.edu/keck/nida/index.aspx). Sample descriptions are compatible with the evolving MIAPE standards.

Proper citation: YPED (RRID:SCR_001436) Copy   

•   Source: SciCrunch Registry

http://amp.pharm.mssm.edu/Enrichr/

A web-based gene list enrichment analysis tool that provides various types of visualization summaries of collective functions of gene lists. It includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes / proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries.

Proper citation: Enrichr (RRID:SCR_001575) Copy   

•   Source: SciCrunch Registry

http://orphelia.gobics.de/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23,2022. A metagenomic open reading frame (ORF) finding tool for the prediction of protein coding genes in short, environmental DNA sequences with unknown phylogenetic origin. The resource is based on a two-stage machine learning approach that uses linear discriminants to extract features from the ORFs. An artificial neural network then combines the features and computes a gene probability for each ORF fragment.

Proper citation: Orphelia (RRID:SCR_000119) Copy   

•   Source: SciCrunch Registry

http://www.gobics.de/fabian/treephyler.php

A software tool for fast taxonomic profiling of metagenomes.

Proper citation: Treephyler (RRID:SCR_000109) Copy   

•   Source: SciCrunch Registry

http://www.arb-home.de/

Software environment for maintaining databases of molecular sequences and additional information, and for analyzing the sequence data, with emphasis on phylogeny reconstruction. Programs have primarily been developed for ribosomal ribonucleic acid (rRNA) sequences and, therefore, contain special tools for alignment and analysis of these structures. However, other molecular sequence data can also be handled. Protein gene sequences and predicted protein primary structures as well as protein secondary structures can be stored in the same database. ARB package is designed for graphical user interface. Program control and data display are available in a hierarchical set of windows and subwindows. Majority of operations can be controlled using mouse for moving pointer and the left mouse button for initiating and performing operations.

Proper citation: ARB project (RRID:SCR_000515) Copy   

•   Source: SciCrunch Registry

http://www.bioextract.org/GuestLogin

An open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet.

Proper citation: BioExtract (RRID:SCR_005397) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/synergizer/translate/

The Synergizer database is a growing repository of gene and protein identifier synonym relationships. This tool facilitates the conversion of identifiers from one naming scheme (a.k.a namespace) to another. The Synergizer is a service for translating between sets of biological identifiers. It can, for example, translate Ensembl Gene IDs to Entrez Gene IDs, or IPI IDs to HGNC gene symbols, and much more. Unlike some other tools for this purpose, The Synergizer is simple and easy to learn. The Synergizer works via a web interface (for users who are not programmers) or through a web service (for programmatic access).

Proper citation: Synergizer (RRID:SCR_005308) Copy   

•   Source: SciCrunch Registry

http://users-birc.au.dk/biopv/php/fabox/

Tools for splitting, joining and otherwise manipulating FASTA format sequence files. The first tools in the toolbox is for manipulating fasta headers, cropping alignments and doing some sequence comparison allowing users to combine the description of data (often in excel spreadsheets) with the actual data (often DNA sequences). Also, producing correct input files for a range of programs seems to be problematic for the average user. Hence, some converters in some of the services have been included as well as some stand-alone converters. The converters are not necessarily meant to provide the final input file, but you''ll get a valid input file for Arlequin, MrBayes etc. - that you may further edit so it suit your needs. This means that you may need to combine several of the tools to finish your handling - but it keeps it relatively simple to use. Please note that FaBox is written in PHP and ONLY RUNS ON A WEBSERVER.

Proper citation: FaBox (RRID:SCR_005350) Copy   

•   Source: SciCrunch Registry

http://www.jcvi.org/cgi-bin/tigrfams/index.cgi

Consists curated multiple sequence alignments, Hidden Markov Models (HMMs) for protein sequence classification, and associated information designed to support automated annotation of (mostly prokaryotic) proteins. Starting with release 10.0, TIGRFAMs models use HMMER3, which provides excellent search speed as well as exquisite search sensitivity. See the "TIGRFAMs Complete Listing" page to review the accession, protein name, model type, and EC number (if assigned) of all models. TIGRFAMs is a member database in InterPro. The HMM libraries and supporting files are available to download and use for free from our FTP site.

Proper citation: TIGRFAMS (RRID:SCR_005493) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/gtr/

Central location for voluntary submission of genetic test information by providers including the test''s purpose, methodology, validity, evidence of the test''s usefulness, and laboratory contacts and credentials. GTR aims to advance the public health and research into the genetic basis of health and disease. GTR is accepting registration of clinical tests for Mendelian disorders, complex tests and arrays, and pharmacogenetic tests. These tests may include multiple methods and may include multiple major method categories such as biochemical, cytogenetic, and molecular tests. GTR is not currently accepting registration of tests for somatic disorders, research tests or direct-to-consumer tests.

Proper citation: Genetic Testing Registry (RRID:SCR_005565) Copy   

•   Source: SciCrunch Registry

http://llama.mshri.on.ca/

The Roth Laboratory is designing and interpreting large-scale experiments to understand pathway structure and its relationship to phenotype and human disease. Software for research focused on a specific research goal is available. Current experimental interests: * Exploiting parallel sequencing technology to phenotype all pairwise gene deletion combinations in S. cerevisiae, with initial application to genes involved in transcription. * Generation of S. cerevisiae strains carrying dozens of chosen targeted deletions, with initial application to delete all ABC transporters imparting multidrug resistance. * Targeted insertion of gene sets encoding entire human pathways into S. cerevisiae, with initial application to genes involved in drug metabolism. Current computational interests: * Systematic analysis of genetic interaction to reveal redundant systems and order of action in genetic pathways * Integrating large-scale studies - including phenotype, genetic epistasis, protein-protein and transcription-regulatory interactions and sequence patterns - to quantitatively assign function to genes and guide experimentation and disease association studies. * Alternative splicing and its relationship to protein interaction networks.

Proper citation: Roth Laboratory (RRID:SCR_005711) Copy   

•   Source: SciCrunch Registry

http://genemania.org/

Data analysis service to predict the function of your favorite genes and gene sets. Indexing 1,421 association networks containing 266,984,699 interactions mapped to 155,238 genes from 7 organisms. GeneMANIA interaction networks are available for download in plain text format. GeneMANIA finds other genes that are related to a set of input genes, using a very large set of functional association data. Association data include protein and genetic interactions, pathways, co-expression, co-localization and protein domain similarity. You can use GeneMANIA to find new members of a pathway or complex, find additional genes you may have missed in your screen or find new genes with a specific function, such as protein kinases. Your question is defined by the set of genes you input. If members of your gene list make up a protein complex, GeneMANIA will return more potential members of the protein complex. If you enter a gene list, GeneMANIA will return connections between your genes, within the selected datasets. GeneMANIA suggests annotations for genes based on Gene Ontology term enrichment of highly interacting genes with the gene of interest. GeneMANIA is also a gene recommendation system. GeneMANIA is also accessible via a Cytoscape plugin, designed for power users. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: GeneMANIA (RRID:SCR_005709) Copy   

•   Source: SciCrunch Registry

http://www.molgen.de

The research of the group concentrates on the molecular biology of Gram-positive bacteria, with Bacillus subtilis and Lactococcus lactis as the main model organisms. A number of important (human) pathogens are also investigated: Bacillus cereus, Streptococcus pneumoniae and Enterococcus faecalis. The nature of the research is both fundamental and application-oriented. Transcript- and protein profiling by high-throughput technologies such as DNA microarrays and proteomics tools are being used. The very large data sets generated are analyzed by employing existing and novel bioinformatics tools. Major lines of research are in the field of functional genomics of these organisms, using systems- and synthetic biology approaches.

Proper citation: MolGen (RRID:SCR_005700) Copy   

•   Source: SciCrunch Registry

http://agbase.msstate.edu/cgi-bin/tools/goprofiler_select.pl

Service that provides a summary of GO annotations available for each species. The user provides a taxon id and GOProfiler displays the number of GO associations and the number of annotated proteins for that species. The results are listed by evidence code and a separate list of unannotated proteins is also provided.

Proper citation: GOProfiler (RRID:SCR_005683) Copy   

•   Source: SciCrunch Registry