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http://ambermd.org/

Software package of molecular simulation programs. It is distributed into AmberTools15 and Amber14. AmberTools15 is a software package which can carry out complete molecular dynamics simulations with either explicit water or generalized Born solvent models. It is distributed in source code format and must be compiled in order to be used. Amber14 builds on AmberTools15 by adding the pmemd program, which provides better performance on multiple CPUs and dramatic speed improvements on GPUs compared to sander (molecular dynamics). GPU info, manuals, and tutorials are available on the website.

Proper citation: Assisted Model Building with Energy Refinement (AMBER) (RRID:SCR_014230) Copy   

•   Source: SciCrunch Registry

https://github.com/MikkelSchubert/paleomix

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Software toolkit for the processing of ancient and modern HTS data. PALEOMIX also aids in metagenomic analysis of the extracts from the HTS processing.

Proper citation: PALEOMIX (RRID:SCR_015057) Copy   

•   Source: SciCrunch Registry

https://nels.bioinfo.no

Web portal for the administration of Norwegian e-Infrastructure for Life Sciences. Enables Norwegian life scientists and their international collaborators to store, share, archive, and analyse their genomics scale data. NeLS is one of the packages of the ELIXIR.NO project.

Proper citation: NeLS (RRID:SCR_016301) Copy   

•   Source: SciCrunch Registry

https://web.stanford.edu/group/pritchardlab/structure.html

Software package for using multi locus genotype data to investigate population structure. Used for inferring presence of distinct populations, assigning individuals to populations, studying hybrid zones, identifying migrants and admixed individuals, and estimating population allele frequencies in situations where many individuals are migrants or admixed. Can be applied to most of commonly used genetic markers, including SNPS, microsatellites, RFLPs and Amplified Fragment Length Polymorphisms.

Proper citation: STRUCTURE (RRID:SCR_017637) Copy   

•   Source: SciCrunch Registry

https://github.com/Brazelton-Lab/seq-annot

Software Python package for annotating and counting genomic features in genomes and metagenomes. Software tools to facilitate annotation and comparison of genomes and metagenomes.

Proper citation: seq-annot (RRID:SCR_018731) Copy   

•   Source: SciCrunch Registry

https://qupath.github.io/

Open Source software package for digital pathology image analysis. Used for whole slide image analysis and digital pathology. Provides researchers with batch processing and scripting functionality, and extensible platform with which to develop and share new algorithms to analyze complex tissue images.

Proper citation: QuPath (RRID:SCR_018257) Copy   

•   Source: SciCrunch Registry

https://chlorobox.mpimp-golm.mpg.de/geseq.html

Software tool for rapid and accurate annotation of organelle genomes, in particular chloroplast genomes.

Proper citation: GeSeq (RRID:SCR_017336) Copy   

•   Source: SciCrunch Registry

http://pubcrawler.gen.tcd.ie/

PubCrawler is a free alerting service that scans daily updates to the NCBI Medline (PubMed) and GenBank databases. PubCrawler helps keeping scientists informed of the current contents of Medline and GenBank, by listing new database entries that match their research interests. The free PubCrawler web service has been operating for five years and so far has brought literature and sequence updates to over 22 000 users. It provides information on a personalized web page whenever new articles appear in PubMed or when new sequences are found in GenBank that are specific to customized queries. The server also acts as an automatic alerting system by sending out short notifications or emails with the latest updates as soon as they become available. PubCrawler searches the NCBI PubMed (Medline) and Entrez (GenBank) databases daily using search parameters (keywords, author names, etc.) specified by the user. There is no limit on the number of searches that can be carried out. Previous search hits are stored and only the newest PubMed or GenBank records are shown each day. The results are presented as an HTML Web page, similar to the results of an NCBI PubMed or Entrez query. This Web page can be located on our computer (the PubCrawler WWW-Service), on your computer (the stand-alone program), or you can receive it via e-mail (set this up using the PubCrawler WWW-Service). The Web page sorts the results into groups of PubMed/GenBank entries that are zero-days-old, 1-day-old, 2-days-old, etc., up to a user-specified age limit. Sponsors: Development of PubCrawler was supported by EMBnet

Proper citation: PubCrawler (RRID:SCR_008235) Copy   

•   Source: SciCrunch Registry

https://ccg.murdoch.edu.au/yabi/login/?next=/yabi/

A web-based analytical environment framework for bioinformatics applications that can be customized for a diverse range of -omics applications. The software system is adaptable to a range of both pluggable execution and data backends in an open source implementation. Enabling seamless and transparent access to heterogenous HPC environments at its core, it then provides an analysis workflow environment that can create and reuse workflows as well as manage large amounts of both raw and processed data in a secure and flexible way across geographically distributed compute resources. Yabi can be used via a web-based environment to drag-and-drop tools to create sophisticated workflows. It can also be accessed through the Yabi command line which is designed for users that are more comfortable with writing scripts or for enabling external workflow environments to leverage the features in Yabi. Configuring tools can be a significant overhead in workflow environments. Yabi greatly simplifies this task by enabling system administrators to configure as well as manage running tools via a web-based environment and without the need to write or edit software programs or scripts.

Proper citation: Yabi (RRID:SCR_005359) Copy   

•   Source: SciCrunch Registry

https://imdevsoftware.wordpress.com/imdev/

A software application of RExcel that integrates R into Excel as an embedded additon for omics tasks and analysis. It can be used specifically for tasks concerning multivariate data visualization, exploration, and analysis. imDev has interactive modules for dimensional reduction, prediction, feature selection, analysis of correlation, and generation of networked structures, all of which provide an integrated environment for systems level analysis of multivariate data.

Proper citation: imDEV (RRID:SCR_014674) Copy   

•   Source: SciCrunch Registry

http://www.tassdb.info/

TassDB stores extensive data about alternative splice events at GYNGYN donors and NAGNAG acceptors. Currently, 114,554 tandem splice sites of eight species are contained in the database, 5,209 of which have EST/mRNA evidence for alternative splicing. Users can search by Transcript Accession Number and Gene Symbol, SQL Query, and Tandem Donor/Tandem Acceptor pairs.

Proper citation: TAndem Splice Site DataBase (RRID:SCR_007961) Copy   

•   Source: SciCrunch Registry

http://sisyphus.mrc-cpe.cam.ac.uk

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. A collection of manually curated protein structural alignments and their interrelationships. Each multiple alignment within the SISYPHUS database consists of structurally similar regions common to a group of proteins. These regions range from oligomeric biological units, or individual domains to fragments of different size representing either internal structural repeats or motifs common to structurally distinct proteins. The SISYPHUS multiple alignments are displayed with SPICE, a browser that provides an integrated view of protein sequences, structures and their annotations.

Proper citation: SISYPHUS (RRID:SCR_007930) Copy   

•   Source: SciCrunch Registry

http://silkworm.genomics.org.cn/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 20,2019.A database of integrated genome resources for the silkworm, Bombyx mori. This database provides access to not only genomic data including functional annotation of genes, gene products and chromosomal mapping, but also extensive biological information such as microarray expression data, ESTs and corresponding references. SilkDB will be useful for the silkworm research community as well as comparative genomics. Recently, an international collaboration has been launched to assemble a complete silkworm genome sequence, which is based on the 6� and 3� draft genome sequences created by Chinese group and Japanese group in 2004 (Mita et al., 2004; Xia et al., 2004), respectively. The genome assembly quality has been greatly improved. Base on a high density SNP genetic map, over 80% of genome sequence could be mapped on 28 chromosomes of the silkworm. The first version of SilkDB was released in 2004. Since that time, the silkworm has become a focus in insect research community and the study of silkworm has been greatly accelerated. Now, we are happy to announce the release of a new version of SilkDB, which updated all of the data, added new information of genome sequence and genes, and provides new tools to facilitate use of the genome database.

Proper citation: SilkDB (RRID:SCR_007926) Copy   

•   Source: SciCrunch Registry

http://www.bioinformatics2.wsu.edu/cgi-bin/Athena/cgi/home.pl

Athena is a web-based application that warehouses disparate datatypes related to the control of gene expression. Athena provides several features to enable exploration of the regulatory mechanisms of Arabidopsis gene control. The first main tool we provide is visualization of promoter domains of selected genes. Database crossreference for these transcription factors is provided as well as a statistical test for enrichment of binding activity within the set of selected promoters. The data mining tools in Athena allow for selection of sets of genes based on two different factors. -Genes can be select by specifying a set of binding factors whose putative sites must be present within all of those genes'' promoter regions. -Alternatively, genes can be selected using Gene Ontology annotations. Both GO (Gene Ontology) Slim terms and Gene Ontology terms are available. One can select a set of genes by either choosing a union of the genes annotated by a selected set of Slim terms or Gene Ontology terms. The selected gene''s putative binding factors are listed, including enrichment data. Furthermore, enriched presence of Gene Ontology terms is given. The analysis suite provides both enhanced data mining tools for selecting genes as well as several data displays., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Athena (RRID:SCR_008110) Copy   

•   Source: SciCrunch Registry

http://andromeda.gsf.de/litminer

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The LitMiner software is a literature data-mining tool that facilitates the identification of major gene regulation key players related to a user-defined field of interest in PubMed abstracts. The prediction of gene-regulatory relationships is based on co-occurrence analysis of key terms within the abstracts. LitMiner predicts relationships between key terms from the biomedical domain in four categories (genes, chemical compounds, diseases and tissues). The usefulness of the LitMiner system has been demonstrated recently in a study that reconstructed disease-related regulatory networks by promoter modeling that was initiated by a LitMiner generated primary gene list. To overcome the limitations and to verify and improve the data, we developed WikiGene, a Wiki-based curation tool that allows revision of the data by expert users over the Internet. It is based on the annotation of key terms in article abstracts followed by statistical co-citation analysis of annotated key terms in order to predict relationships. Key terms belonging to four different categories are used for the annotation process: -Genes: Names of genes and gene products. Gene name recognition is based on Ensembl . Synonyms and aliases are resolved. -Chemical Compounds: Names of chemical compounds and their respective aliases. -Diseases and Phenotypes: Names of diseases and phenotypes -Tissues and Organs: Names of tissues and organs LitMiner uses a database of disease and phenotype terms for literature annotation. Currently, there are 2225 diseases or phenotypes, 801 tissues and organs, and 10477 compounds in the database.

Proper citation: LitMiner (RRID:SCR_008200) Copy   

•   Source: SciCrunch Registry

http://dnatraffic.ibb.waw.pl/

DNAtraffic database is dedicated to be an unique comprehensive and richly annotated database of genome dynamics during the cell life. DNAtraffic contains extensive data on the nomenclature, ontology, structure and function of proteins related to control of the DNA integrity mechanisms such as chromatin remodeling, DNA repair and damage response pathways from eight model organisms commonly used in the DNA-related study: Homo sapiens, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Escherichia coli and Arabidopsis thaliana. DNAtraffic contains comprehensive information on diseases related to the assembled human proteins. Database is richly annotated in the systemic information on the nomenclature, chemistry and structure of the DNA damage and drugs targeting nucleic acids and/or proteins involved in the maintenance of genome stability. One of the DNAtraffic database aim is to create the first platform of the combinatorial complexity of DNA metabolism pathway analysis. Database includes illustrations of pathway, damage, protein and drug. Since DNAtraffic is designed to cover a broad spectrum of scientific disciplines it has to be extensively linked to numerous external data sources. Database represents the result of the manual annotation work aimed at making the DNAtraffic database much more useful for a wide range of systems biology applications. DNAtraffic database is freely available and can be queried by the name of DNA network process, DNA damage, protein, disease, and drug.

Proper citation: DNAtraffic (RRID:SCR_008886) Copy   

•   Source: SciCrunch Registry

http://pbil.univ-lyon1.fr/databases/homolens.php

Database of homologous genes from Ensembl organisms, structured under ACNUC sequence database management system. It allows to select sets of homologous genes among species, and to visualize multiple alignments and phylogenetic trees. It is possible to search for orthologous genes in a wide range of taxons. HOMOLENS is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generally, HOMOLENS gives an overall view of what is known about a peculiar gene family. Note that HOMOLENS is split into two databases on this server: HOMOLENS contains the protein sequences while HOMOLENSDNA contains the nucleotide sequences. Protein sequences of HOMOLENS have been generated by translating the CDS of HOMOLENSDNA and using associated cross-references to generate the annotations.

Proper citation: Homologous Sequences in Ensembl Animal Genomes (RRID:SCR_008356) Copy   

•   Source: SciCrunch Registry

http://rsat.ulb.ac.be/rsat/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Retrieve-ensembl-seq is included in the software suite regulatory sequence analysis tools (RSAT), allowing instant submission of retrieved sequences to further analysis tools. AVAILABILITY: retrieve-ensembl-seq is integrated in the RSAT suite: http://rsat.ulb.ac.be/rsat. Web site: http://rsat.ulb.ac.be/rsat/retrieve-ensembl-seq_form.cgi. Web services: http://rsat.ulb.ac.be/rsat/web_services/RSATWS.wsdl. Stand-alone distribution: freely available under an academic licence to download from the RSAT web site. The complete manual, a convenient tutorial and demos are available from the RSAT website. Additional help can be found on the RSAT public forum.

Proper citation: Regulatory Sequence Analysis Tools (RRID:SCR_008560) Copy   

•   Source: SciCrunch Registry

http://gump.qimr.edu.au/general/daleN/SNPSpD/

SNPSpD is a method of correcting for non-independance of single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of LD between SNP''s. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor loadings after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.

Proper citation: Single Nucleotide Polymorphism Spectral Decomposition (SNPSpD) (RRID:SCR_008621) Copy   

•   Source: SciCrunch Registry

http://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/

WebProAnalyst provides web-accessible analysis for scanning the quantitative structure-activity relationships in protein families. It searches for a sequence region, whose substitutions are correlated with variations in the activities of a homologous protein set, the so-called activity modulating sites. WebProAnalyst allows users to search for the key physicochemical characteristics of the sites that affect the changes in protein activities. It enables the building of multiple linear regression and neural networks models that relate these characteristics to protein activities. WebProAnalyst implements multiple linear regression analysis, back propagation neural networks and the Structure-Activity Correlation/Determination Coefficient (SACC/SADC). A back propagation neural network is implemented as a two-layered network, one layer as input, the other as output (Rumelhart et al, 1986). WebProAnalyst uses alignment of amino acid sequences and data on protein activity (pK, Km, ED50, among others). The input data are the numerical values for the physicochemical characteristics of a site in the multiple alignment given by a slide window. The output data are the predicted activity values. The current version of WebProAnalyst handles a single activity for a single protein. The SACC/SADC may be defined as an estimate of the strongest multiple correlation between the physicochemical characteristics of a site in a multiple alignment and protein activities. The SACC/SADC coefficient makes possible the calculation of the possible highest correlation achievable for the quantitative relationship between the physicochemical properties of sites and protein activities. The SACC/SADC is a convenient means for an arrangement of positions by their functional significance. WebProAnalyst outputs a list of multiple alignment positions, the respective correlation values, also regression analysis parameters for the relationships between the amino acid physicochemical characteristics at these positions and the protein activity values.

Proper citation: Webproanalyst (RRID:SCR_008348) Copy   

•   Source: SciCrunch Registry