Tools   Select Another Resource Report Type

http://www.homepages.ed.ac.uk/pmckeigu/admixmap/index.html

General-purpose program for modelling admixture, using marker genotypes and trait data on a sample of individuals from an admixed population (such as African-Americans), where the markers have been chosen to have extreme differentials in allele frequencies between two or more of the ancestral populations between which admixture has occurred. The main difference between ADMIXMAP and classical programs for estimation of admixture such as ADMIX is that ADMIXMAP is based on a multilevel model for the distribution of individual admixture in the population and the stochastic variation of ancestry on hybrid chromosomes. This makes it possible to model the associations of ancestry between linked marker loci, and the association of a trait with individual admixture or with ancestry at a linked marker locus. (entry from Genetic Analysis Software)

Proper citation: ADMIXMAP (RRID:SCR_009035) Copy   

•   Source: SciCrunch Registry

https://github.com/gaow/genetic-analysis-software/blob/master/pages/MOSCPHASER.md

THIS RESOURCE IS NO LONGER IN SERVICE, documented September 29, 2016. Software application for inferring haplotypes composed of both CNV alleles and SNP alleles.

Proper citation: MOSCPHASER (RRID:SCR_009092) Copy   

•   Source: SciCrunch Registry

https://github.com/gaow/genetic-analysis-software/blob/master/pages/GLUE.md

THIS RESOURCE IS NO LONGER IN SERVCE, documented September 6, 2016. A web interface to several commonly used statistical genetics programs, including Linkage, Genehunter, Merlin, Unphased, and Transmit. It simplifies their use through graphical selection of program options, automation of multiple analyses, and viewing of graphical output. GLUE is available to HGMP account holders; registration is free to all academic users., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GLUE (RRID:SCR_009211) Copy   

•   Source: SciCrunch Registry

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

Software application that is a statistical method that bridges the gap between single-locus and haplotype-based tests of association. It is based on the non-parametric regression techniques embodied by Bayesian Adaptive Regression Splines. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: BARS (RRID:SCR_009123) Copy   

•   Source: SciCrunch Registry

https://knights-lab.github.io/MLRepo/

Machine learning repository for microbiome datasets.

Proper citation: ML Repo (RRID:SCR_017079) Copy   

•   Source: SciCrunch Registry

http://steps.sourceforge.net/STEPS/default.php

STEPS is a package for exact stochastic simulation of reaction-diffusion systems in realistic, complex 3D geometries. Our core simulation algorithm is an efficient implementation of a variation on Gillespie''s SSA, extended to deal with diffusion of molecules over the elements of a 3D tetrahedral mesh. While it was mainly developed for simulating detailed models of neuronal signaling pathways in dendrites and around synapses, it is a general tool and can be used for studying any biochemical pathway in which spatial gradients and morphology are thought to play a role. We have implemented STEPS as a set of Python modules, which means STEPS users can use Python scripts to control all aspects of setting up the model, generating a mesh, controlling the simulation and generating and analyzing output. The core computational routines are still implemented as C/C++ extension modules for maximal speed of execution.

Proper citation: STEPS (RRID:SCR_008742) Copy   

•   Source: SciCrunch Registry

http://www.genoscope.cns.fr/gmove

Software tool for genome annotation. Eukaryotic gene prediction tool focused on evidence supported by expressed sequences like transcripts and conserved proteins alignments. Can be used to reannotate genomes, to do comparative gene prediction and improve existing genome annotation. Can predict gene models with canonical and non-canonical splice sites.

Proper citation: Gmove (RRID:SCR_019132) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/simvascular

Open source software suite for cardiovascular simulation. It includes code for reading 3D images, segmenting structures, generating models and meshes, and modeling blood flow in deformable vessels. The suite also includes tools for physiologic boundary conditions, fluid structure interaction, and an accurate and efficient finite element Navier-Stokes solver. Commercial components have been used in the simulation process, and for these components, the project attempts to provide interfaces that allow substitution of open source components. The SimVascular project is derived from the ASPIRE2 software project and includes modified portions of PHASTA from RPI/SCOREC.

Proper citation: SimVascular (RRID:SCR_002686) Copy   

•   Source: SciCrunch Registry

http://www.nest-simulator.org/

Software tool as simulator for spiking neural network models that focuses on dynamics, size and structure of neural systems rather than on exact morphology of individual neurons. Used for any size spiking neurons networks including models of information processing, models of network activity dynamics, models of learning and plasticity.

Proper citation: NEST Simulator (RRID:SCR_002963) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/pybel

Software Python package for parsing, validating, compiling, and converting networks encoded in Biological Expression Language.Package consists of network data container, parser and validator, network database manager, data converter and network visualizer. Computational framework for Biological Expression Language. Used to pars BEL documents, validate their semantics, and facilitate data interchange between common formats and database systems like JSON, CSV, Excel, SQL, CX, and Neo4J.

Proper citation: PyBEL (RRID:SCR_017660) Copy   

•   Source: SciCrunch Registry

http://www.jstacs.de/index.php/GeMoMa

Software tool as homology based gene prediction program that predicts gene models in target species based on gene models in evolutionary related reference species. Utilizes amino acid sequence conservation, intron position conservation, and RNA-seq data to accurately predict protein-coding transcripts. Supports combination of predictions based on several reference species allowing to transfer high quality annotation of different reference species to target species.

Proper citation: GeMoMa (RRID:SCR_017646) Copy   

•   Source: SciCrunch Registry

https://github.com/zhanxw/MB-GAN

Software tool as deep learning simulation framework for simulating realistic microbiome data. Can automatically learn from given microbial abundances and compute simulated abundances that are indistinguishable from it.

Proper citation: MB-GAN (RRID:SCR_019289) Copy   

•   Source: SciCrunch Registry

http://pilgrm.princeton.edu

PILGRM (the platform for interactive learning by genomics results mining) puts advanced supervised analysis techniques applied to enormous gene expression compendia into the hands of bench biologists. This flexible system empowers its users to answer diverse biological questions that are often outside of the scope of common databases in a data-driven manner. This capability allows domain experts to quickly and easily generate hypotheses about biological processes, tissues or diseases of interest. Specifically PILGRM helps biologists generate these hypotheses by analyzing the expression levels of known relevant genes in large compendia of microarray data. PILGRM is for the biologist with a set of proteins relevant to a disease, biological function or tissue of interest who wants to find additional players in that process. It uses a data driven method that provides added value for literature search results by mining compendia of publicly available gene expression datasets using lists of relevant and irrelevant genes (standards). PILGRM produces publication quality PDFs usable as supplementary material to describe the computational approach, standards and datasets. Each PILGRM analysis starts with an important biological question (e.g. What genes are relevant for breast cancer but not mammary tissue in general?). For PILGRM to discover relevant genes, it needs examples of both genes that you would (positive) and would not (negative) find interesting. Lists of these genes are what we call standards and in PILGRM you can build your own standards or you can use standards from common sources that we pre-load for your convenience. PILGRM lets you build your own literature-documented standards so that processes, disease, and tissues that are not well covered in databases of tissue expression, disease, or function can still be used for an analysis.

Proper citation: PILGRM (RRID:SCR_004749) Copy   

•   Source: SciCrunch Registry

http://swift.cmbi.ru.nl/gv/hssp/

HSSP (homology-derived structures of proteins) is a derived database merging structural (2-D and 3-D) and sequence information (1-D). For each protein of known 3D structure from the Protein Data Bank, the database has a file with all sequence homologues, properly aligned to the PDB protein. Homologues are very likely to have the same 3D structure as the PDB protein to which they have been aligned. As a result, the database is not only a database of sequence aligned sequence families, but it is also a database of implied secondary and tertiary structures. Likely secondary structure are carried over from the PDB protein to each homologous protein. Tertiary structure models can be built by fitting the sequence of the homologue as aligned into the 3D template of the protein of known structure. Special software is needed to construct 3D models by homology, such WHATIF by Gert Vriend or MaxSprout by Liisa Holm and Chris Sander. The command rsync can be used to obtain a local copy of the HSSP. We appreciate receiving an Email from people who do so, but there are no strings attached. Everybody can freely download the files, academia and industry alike. If your institute''s firewall doesn''t allow you to use the (preferred) rsync way of obtaining HSSP files, feel free to work with FTP. The files are in that case available from: ftp://ftp.cmbi.ru.nl//pub/molbio/data/hssp/

Proper citation: HSSP (RRID:SCR_004953) Copy   

•   Source: SciCrunch Registry

http://sms.cbi.cnptia.embrapa.br/SMS/STINGm/SMSReport/

Sting Report is a database of amino acid sequences, structures, functions, and parameters. It allows users to easily extract from the Blue Star Sting Database detailed but focused information about an individual amino acid, which belongs to a structure described in a PDB file. The extracted information is presented as a series of GIF images and a table, which are generated by Blue Star Sting modules and contain values of up to 125 sequence/structure/function descriptors/parameters. The HTML page resulting from a query on Sting Report, containing the GIF images and the table, is printable, and can also be composed and visualized at a computer platform with elementary configuration.

Proper citation: STING Report (RRID:SCR_005121) Copy   

•   Source: SciCrunch Registry

http://www.ihop-net.org/UniPub/iHOP/

Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.

Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy   

•   Source: SciCrunch Registry

http://spot.cgsmd.isi.edu

A web-based tool for using biological databases to prioritize single nucleotide polymorphisms (SNPs) after a genome-wide association study (GWAS). The site allows users to upload a list of SNPs and GWAS P-values and returns a prioritized list of SNPs using the GIN method. Users can specify candidate genes or genomic regions with custom levels of prioritization. The results can be downloaded or viewed in the browser where users can interactively explore the details of each SNP, including graphical representations of the genomic information network (GIN) method. For investigators interested in incorporating biological databases into a post-GWAS SNP selection strategy, the SPOT web tool is an easily implemented and flexible solution.

Proper citation: SPOT - Biological prioritization after a SNP association study (RRID:SCR_005193) Copy   

•   Source: SciCrunch Registry

http://metagenomics.anl.gov/

An automated analysis platform for metagenomes providing quantitative insights into microbial populations based on sequence data. The server primarily provides upload, quality control, automated annotation and analysis for prokaryotic metagenomic shotgun samples.

Proper citation: MG-RAST (RRID:SCR_004814) Copy   

•   Source: SciCrunch Registry

http://www.gomapman.org/

An open web-accessible resource for gene functional annotations in the plant sciences to facilitate improvement, consolidation and visualization of gene annotations across several plant species. It is based on the MapMan ontology, organized in the form of a hierarchical tree of biological concepts, which describe gene functions. Currently, genes of the model species Arabidopsis, potato, tomato, rice, and tobacco are included. The main features are (i) dynamic and interactive gene product annotation through various curation options; (ii) consolidation of gene annotations for different plant species through the integration of orthologue group information; (iii) traceability of gene ontology changes and annotations; (iv) integration of external knowledge about genes from different public resources; and (v) providing gathered information to high-throughput analysis tools via dynamically generated export files. All of the GoMapMan functionalities are openly available, with the restriction on the curation functions, which require prior registration to ensure traceability of the implemented changes.

Proper citation: GoMapMan (RRID:SCR_005060) Copy   

•   Source: SciCrunch Registry