Tools   Select Another Resource Report Type

http://hgc.rockefeller.edu/

An interactive web server that enables researchers to prioritize any list of genes by their biological proximity to defined core genes (i.e. genes that are known to be associated with the phenotype), and to predict novel gene pathways.

Proper citation: Human Gene Connectome Server (RRID:SCR_002627) Copy   

•   Source: SciCrunch Registry

http://mltreemap.org/

Data analysis service that analyzes DNA sequences and determines their most likely phylogenetic origin. Its main use is in metagenomics projects, where DNA is isolated directly from natural environments and sequenced (the organisms from which the DNA originates are often entirely undescribed). It will search such sequences for suitable marker genes, and will use maximum likelihood analysis to place them in the ''''Tree of Life''''. This placement is more reliable than simply assessing the closest relative of a sequence using BLAST. More importantly, MLTreeMap decides not only who is the closest relative of your query sequence, but also how deep in the tree of life it probably branched off. Additionally, MLTreeMap searches the sequences for genes, which are coding for key enzymes of important functional pathways, such as RuBisCo, methane monooxygenase or nitrogenase. In case of a positive hit, MLTreeMap uses maximum likelihood analysis to place them in the respective ''''gene-family tree''''.

Proper citation: MLTreeMap (RRID:SCR_004792) Copy   

•   Source: SciCrunch Registry

https://reich.hms.harvard.edu/software

Software application that finds skews in ancestry that are potentially associated with disease genes in recently mixed populations like African Americans. It can be downloaded for either UNIX or Linux.

Proper citation: Ancestrymap (RRID:SCR_004353) Copy   

•   Source: SciCrunch Registry

http://amphoranet.pitgroup.org/

Webserver implementation of the AMPHORA2 workflow for phylogenetic analysis of metagenomic shotgun sequencing data. It is capable of assigning a probability-weighted taxonomic group for each phylogenetic marker gene found in the input metagenomic sample.

Proper citation: AmphoraNet (RRID:SCR_005009) Copy   

•   Source: SciCrunch Registry

http://webclu.bio.wzw.tum.de/profcom/

Profiling of Complex Functionality (ProfCom) is a web-based tool for the functional interpretation of a gene list that was identified to be related by experiments. A trait which makes ProfCom a unique tool is an ability to profile enrichments of not only available Gene Ontology (GO) terms but also of complex function. A complex function is constructed as Boolean combination of available GO terms. The complex functions inferred by ProfCom are more specific in comparison to single terms and describe more accurately the functional role of genes. Platform: Online tool

Proper citation: ProfCom - Profiling of complex functionality (RRID:SCR_005797) Copy   

•   Source: SciCrunch Registry

http://estbioinfo.stat.ub.es/apli/serbgov131/index.php

SerbGO is a web-based tool intended to assist researchers determine which microarray tools for gene expression analysis which make use of the GO ontologies are best suited to their projects. SerbGO is a bidirectional application. The user can ask for some features by checking on the Query Form to get the appropriate tools for their interests. The user can also compare tools to check which features are implemented in each one. Platform: Online tool

Proper citation: SerbGO (RRID:SCR_005798) Copy   

•   Source: SciCrunch Registry

http://katahdin.mssm.edu/kismeth/revpage.pl

A web-based tool for bisulfite sequencing analysis that was designed to be used with plants, since it considers potential cytosine methylation in any sequence context (CG, CHG, and CHH). It provides a tool for the design of bisulfite primers as well as several tools for the analysis of the bisulfite sequencing results. Kismeth is not limited to data from plants, as it can be used with data from any species.

Proper citation: Kismeth (RRID:SCR_005444) Copy   

•   Source: SciCrunch Registry

http://omicslab.genetics.ac.cn/GOEAST/

Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods. Compared with available GO analysis tools, GOEAST has the following unique features: * GOEAST supports analysis for data from various resources, such as expression data obtained using Affymetrix, illumina, Agilent or customized microarray platforms. GOEAST also supports non-microarray based experimental data. The web-based feature makes GOEAST very user friendly; users only have to provide a list of genes in correct formats. * GOEAST provides visualizable analysis results, by generating graphs exhibiting enriched GO terms as well as their relationships in the whole GO hierarchy. * Note that GOEAST generates separate graph for each of the three GO categories, namely biological process, molecular function and cellular component. * GOEAST allows comparison of results from multiple experiments (see Multi-GOEAST tool). The displayed color of each GO term node in graphs generated by Multi-GOEAST is the combination of different colors used in individual GOEAST analysis. Platform: Online tool

Proper citation: GOEAST - Gene Ontology Enrichment Analysis Software Toolkit (RRID:SCR_006580) Copy   

•   Source: SciCrunch Registry

http://gopubmed.org/web/gopubmed/

A web server which allows users to explore PubMed search results with the Gene Ontology, a hierarchically structured vocabulary for molecular biology. GoPubMed submits a user''''s keywords to PubMed, retrieves the abstracts, detects Gene Ontology terms in the abstracts, displays the subset of Gene Ontology relevant to the original query, and allows the user to browse through the ontology displaying associated papers and their GO annotation. Platform: Online tool

Proper citation: GoPubMed (RRID:SCR_005823) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/expressionprofiler/

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. The EP:GO browser is built into EBI's Expression Profiler, a set of tools for clustering, analysis and visualization of gene expression and other genomic data. With it, you can search for GO terms and identify gene associations for a node, with or without associated subnodes, for the organism of your choice.

Proper citation: Expression Profiler (RRID:SCR_005821) Copy   

•   Source: SciCrunch Registry

http://pir.georgetown.edu/pirwww/dbinfo/pirsf.shtml

A SuperFamily classification system, with rules for functional site and protein name, to facilitate the sensible propagation and standardization of protein annotation and the systematic detection of annotation errors. The PIRSF concept is being used as a guiding principle to provide comprehensive and non-overlapping clustering of UniProtKB sequences into a hierarchical order to reflect their evolutionary relationships. The PIRSF classification system is based on whole proteins rather than on the component domains; therefore, it allows annotation of generic biochemical and specific biological functions, as well as classification of proteins without well-defined domains. There are different PIRSF classification levels. The primary level is the homeomorphic family, whose members are both homologous (evolved from a common ancestor) and homeomorphic (sharing full-length sequence similarity and a common domain architecture). At a lower level are the subfamilies which are clusters representing functional specialization and/or domain architecture variation within the family. Above the homeomorphic level there may be parent superfamilies that connect distantly related families and orphan proteins based on common domains. Because proteins can belong to more than one domain superfamily, the PIRSF structure is formally a network. The FTP site provides free download for PIRSF.

Proper citation: PIRSF (RRID:SCR_003352) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/pride/

Centralized, standards compliant, public data repository for proteomics data, including protein and peptide identifications, post-translational modifications and supporting spectral evidence. Originally it was developed to provide a common data exchange format and repository to support proteomics literature publications. This remit has grown with PRIDE, with the hope that PRIDE will provide a reference set of tissue-based identifications for use by the community. The future development of PRIDE has become closely linked to HUPO PSI. PRIDE encourages and welcomes direct user submissions of protein and peptide identification data to be published in peer-reviewed publications. Users may Browse public datasets, use PRIDE BioMart for custom queries, or download the data directly from the FTP site. PRIDE has been developed through a collaboration of the EMBL-EBI, Ghent University in Belgium, and the University of Manchester.

Proper citation: Proteomics Identifications (PRIDE) (RRID:SCR_003411) Copy   

•   Source: SciCrunch Registry

http://www.ichip.de/software/SplicingCompass.html

Software for detection of differential splicing between two different conditions using RNA-Seq data.

Proper citation: SplicingCompass (RRID:SCR_003249) Copy   

•   Source: SciCrunch Registry

https://bitbucket.org/dranew/defuse

Software package for gene fusion discovery using RNA-Seq data. It uses clusters of discordant paired end alignments to inform a split read alignment analysis for finding fusion boundaries.

Proper citation: deFuse (RRID:SCR_003279) Copy   

•   Source: SciCrunch Registry

http://www.cellimagelibrary.org/

Freely accessible, public repository of vetted and annotated microscopic images, videos, and animations of cells from a variety of organisms, showcasing cell architecture, intracellular functionalities, and both normal and abnormal processes. Explore by Cell Process, Cell Component, Cell Type or Organism. The Cell includes images acquired from historical and modern collections, publications, and by recruitment.

Proper citation: Cell Image Library (CIL) (RRID:SCR_003510) Copy   

•   Source: SciCrunch Registry

http://www.reactome.org

Collection of pathways and pathway annotations. The core unit of the Reactome data model is the reaction. Entities (nucleic acids, proteins, complexes and small molecules) participating in reactions form a network of biological interactions and are grouped into pathways (signaling, innate and acquired immune function, transcriptional regulation, translation, apoptosis and classical intermediary metabolism) . Provides website to navigate pathway knowledge and a suite of data analysis tools to support the pathway-based analysis of complex experimental and computational data sets.

Proper citation: Reactome (RRID:SCR_003485) Copy   

•   Source: SciCrunch Registry

http://www.etriks.org/

Research informatics and analytics platform for the IMI OncoTrack consortium.

Proper citation: eTRIKS (RRID:SCR_003765) Copy   

•   Source: SciCrunch Registry

http://cng.gmu.edu:8080/Lm

A freely available software tool available for the Windows and Linux platform, as well as the Online version Applet, for the analysis, comparison and search of digital reconstructions of neuronal morphologies. For the quantitative characterization of neuronal morphology, LM computes a large number of neuroanatomical parameters from 3D digital reconstruction files starting from and combining a set of core metrics. After more than six years of development and use in the neuroscience community, LM enables the execution of commonly adopted analyses as well as of more advanced functions, including: (i) extraction of basic morphological parameters, (ii) computation of frequency distributions, (iii) measurements from user-specified subregions of the neuronal arbors, (iv) statistical comparison between two groups of cells and (v) filtered selections and searches from collections of neurons based on any Boolean combination of the available morphometric measures. These functionalities are easily accessed and deployed through a user-friendly graphical interface and typically execute within few minutes on a set of 20 neurons. The tool is available for either online use on any Java-enabled browser and platform or may be downloaded for local execution under Windows and Linux.

Proper citation: L-Measure (RRID:SCR_003487) Copy   

•   Source: SciCrunch Registry

http://iubio.bio.indiana.edu/webapps/SeWeR/

Sequence analysis using Web Resources (SeWeR) is an integrated, Dynamic HTML (DHTML) interface to commonly used bioinformatics services available on the World Wide Web. It is highly customizable, extendable, platform neutral, completely server-independent and can be hosted as a web page as well as being used as stand-alone software running within a web browser. It doesn''t require any server to host itself. The goal of SeWeR is to turn your web-browser into a powerful sequence-analysis tool. It is written entirely in JavaScript1.2. SeWeR can be downloaded and mirrored freely. The whole package is just around 300K. You can even run it from a floppy. SeWeR is not compatible with Netscape 6. SeWeR now generates graphics. Savvy is a plasmid drawing software that generates plasmid map in the revolutionary Scalable Vector Graphics format from W3C.

Proper citation: SeWeR - SEquence analysis using WEb Resources (RRID:SCR_004167) Copy   

•   Source: SciCrunch Registry

http://hyphy.org/

Open source software package for comparative sequence analysis using stochastic evolutionary models. Used for analysis of genetic sequence data in particular the inference of natural selection using techniques in phylogenetics, molecular evolution, and machine learning.

Proper citation: HyPhy (RRID:SCR_016162) Copy   

•   Source: SciCrunch Registry