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http://www.cs.ucr.edu/~yyang027/mrfseq.htm

Algorithm based on a Markov random field (MRF) model that uses additional gene coexpression data to enhance differential gene expression prediction power. It is able to call differentially expressed (DE) genes but also assign confidence scores to each inferred DE gene.

Proper citation: MRFSEQ (RRID:SCR_002972) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on January 4,2023. IgBLAST was developed at NCBI to facilitate analysis of immunoglobulin V region sequences in GenBank. In addition to performing a regular BLAST search, IgBLAST has several additional functions: - Reports the germline V, D and J gene matches to the query sequence. - Annotates the immunoglobulin domains (FWR1 through FWR3). - Matches the returned hits (for databases other than germline genes) to the closest germline V genes, making it easier to identify related sequences. - Reveals the V(D)J junction details such as nucleotide homology between the ends of V(D)J segments and N nucleotide insertions. D and J gene reporting is only for nucleotide sequence search and requires a stretch of five or more nucleotide identity between the query and D or J genes. Sponsors: This resource is supported by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine.

Proper citation: IgBLAST (RRID:SCR_002873) Copy   

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http://systemsbio.ucsd.edu/GoSurfer/

GoSurfer uses Gene Ontology (GO) information to analyze gene sets obtained from genome-wide computations or microarray analyses. GoSurfer is a graphical interactive data mining tool. It associates user input genes with GO terms and visualizes such GO terms as a hierarchical tree. Users can manipulate the tree output by various means, like setting heuristic thresholds or using statistical tests. Significantly important GO terms resulted from a statistical test can be highlighted. All related information are exportable either as texts or as graphics. Platform: Windows compatible

Proper citation: GoSurfer (RRID:SCR_005789) Copy   

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http://www.bioinfo.no/tools/bomp

BOMP is a tool for prediction of beta-barrel integral outer membrane proteins. The user may submit a list of proteins, and receive a list of predicted BOMPs. The program, called the beta-barrel Outer Membrane protein Predictor (BOMP), is based on two separate components to recognize integral beta-barrel proteins. The first component is a C-terminal pattern typical of many integral beta-barrel proteins. The second component calculates an integral beta-barrel score of the sequence based on the extent to which the sequence contains stretches of amino acids typical of transmembrane -strands. To use the BOMP tool simply paste your fasta-formatted sequences into the text area, or choose a file which contains sequences. Then hit the submit button. It is possible to perform a BLAST search parallel with the predictions, which may be suitable in some cases. Using the BLAST search will however increase the running time substantially. Sponsors: This work was supported in part by grants from the Norwegian Research Council [SUP 140785/420 (GABI); FUGE/CBU151899/ISO], and the Meltzer Foundation, University of Bergen. Keywords: Beta-barrel, Membrane, Protein, Program, Software, Beta strand, Bacteria,

Proper citation: BOMP: beta-barrel Outer Membrane protein Predictor (RRID:SCR_007268) Copy   

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http://tvap.genome.wustl.edu/tools/varscan/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 7,2024. Platform-independent, technology-independent software tool for identifying SNPs and indels in massively parallel sequencing of individual and pooled samples. Given data for a single sample, VarScan identifies and filters germline variants based on read counts, base quality, and allele frequency. Given data for a tumor-normal pair, VarScan also determines the somatic status of each variant (Germline, Somatic, or LOH) by comparing read counts between samples. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VARSCAN (RRID:SCR_006849) Copy   

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http://droog.gs.washington.edu/ldSelect.html

Software program that analyzes patterns of linkage disequilibrium (LD) between polymorphic sites in a locus, and bins the SNPs on the basis of a threshold level of LD as measured by r2. (entry from Genetic Analysis Software), THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: LDSELECT (RRID:SCR_007010) Copy   

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http://mga.bionet.nsc.ru/soft/index.html

Software application that allows drawing pedigrees with a difficult structure, those containing consanguinity loops, and those individuals with multiple mates or several related families (entry from Genetic Analysis Software)

Proper citation: PEDIGREEQUERY (RRID:SCR_009041) Copy   

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http://watson.hgen.pitt.edu/register/soft_doc.html

Software application that is a faster version of SLINK (entry from Genetic Analysis Software)

Proper citation: FASTSLINK (RRID:SCR_008664) Copy   

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http://mga.bionet.nsc.ru/soft/pedpeel/

Software program that prepares pedigree data for calculation of Elston-Stewarts'' likelihood function. It finds an optimal way to peel a pedigree and returns text file containing 7 description arrays (entry from Genetic Analysis Software)

Proper citation: PEDPEEL (RRID:SCR_008436) Copy   

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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   

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https://qgis.org/en/site/

Open source cross platform desktop geographic information system application that supports viewing, editing, and analysis of geospatial data. Functions as geographic information system software, allowing users to analyze and edit spatial information, in addition to composing and exporting graphical maps.

Proper citation: QGIS (RRID:SCR_018507) Copy   

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http://bios.unc.edu/~weisun/software/asSeq.htm

Software that establishes a statistical framework for future developments of eQTL (expression quantitative trait locus) mapping methods using RNA-seq data (e.g., linkage-based eQTL mapping), and the joint study of multiple genetic markers and/or multiple genes. This R package has been submitted to R/bioconductor. It will be available on bioconductor soon. It is recommended to install this R package from bioconductor. You can also install this R package from the source code by yourself. Since the R package contains C code, a C complier is required for installation. With both R and appropriate c complier installed, this R package can be installed using the following command (in Mac Terminal window or Windows command window) R CMD INSTALL asSeq

Proper citation: asSeq (RRID:SCR_001625) Copy   

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https://cran.r-project.org/package=precrec

Software R package for fast and accurate precision recall and ROC curve calculations. Calculates accurate precision recall and Receiver Operator Characteristics curves.

Proper citation: precrec (RRID:SCR_018659) Copy   

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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   

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

Machine learning repository for microbiome datasets.

Proper citation: ML Repo (RRID:SCR_017079) Copy   

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https://hnn.brown.edu/

Open source software package for circuit level interpretation of human EEG/MEG data. Software tool for interpreting cellular and network origin of human MEG/EEG data. Simulates electrical activity of neocortical cells and circuits that generate primary electrical currents underlying EEG/MEG recordings. Designed for researchers and clinicians, without computational neural modeling experience, to develop and test hypothesis on circuit origin of their data.

Proper citation: Human Neocortical Neurosolver (RRID:SCR_017437) Copy   

•   Source: SciCrunch Registry

https://planttfdb.gao-lab.org/

Comprehensive plant transcription factor database. Interface to allow users to search the database by IDs or free texts, to make sequence similarity search against TFs of all or individual species, and to download TF sequences for local analysis.PlantTFDB 3.0: a portal for the functional and evolutionary study of plant transcription factors

Proper citation: PLANTTFDB (RRID:SCR_003362) Copy   

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https://bioconductor.org/packages/genomation/

Software R package for simplfiying common tasks in genomic feature analysis. Toolkit to summarize, annotate and visualize genomic intervals. Provides functions for reading BED and GFF files as GRanges objects, summarizing genomic features over predefined windows so users can make average enrichment of features over defined regions or produce heatmaps. Can annotate given regions with other genomic features such as exons,introns and promoters.

Proper citation: genomation (RRID:SCR_003435) Copy   

•   Source: SciCrunch Registry

http://www.neuromatic.thinkrandom.com/

NeuroMatic is a collection of Igor Pro functions for analyzing electrophysiological data. By allowing users to organize their data into Sets and Groups, NeuroMatic makes it relatively easy to compute transformations and statistical analyses on their data, including scaling, alignment averaging, baseline subtraction, spike detection, stationarity analysis, rise-time computations, etc. Being open source and modular designed, NeuroMatic also allows users to develop their own analysis functions that can be easily incorporated into NeuroMatic's framework. Note, if you have reached this page in search of a freeware tool for neuronal reconstructions, you are more likely to be interested in Neuromantic, a software package that sounds like NeuroMatic, but is not quite the same. Features of NeuroMatic Include * Sorting, Scaling, Averaging, Interpolation * Max / Min / Mean / Level / Rise Time / FWHM / Slope Measurements * Stability / Stationarity Analysis * Event Detection * Waveform Template Matching * Spike Raster Plots * Interspike-Interval and Peri-Stimulus Time (PST) Histograms * Compact Easy-to-Use Interface * Modular design as a basis for your own procedures * Extra space for your own buttons and controls * Import functions for Axograph and Pclamp data * Automatic macro generation for batch processing Supporting Agencies: MRC, Wellcome Trust Spike, Event, Fit, NClamp, Acquisition, spike train, EPSP, IPSP, IPSC, EPSC

Proper citation: NeuroMatic (RRID:SCR_004186) Copy   

•   Source: SciCrunch Registry

http://ratmine.mcw.edu/ratmine/begin.do

RatMine integrates data from RGD, UniProtKB, NCBI, KEGG and other sources to form a web-based data warehouse and tool set tailored for rat based data research. Search RatMine by entering names, identifiers, or keywords for genes, proteins, pathways, papers, etc. Additionally, we support programmatic access to our data through Application Programming Interface - choose from Perl or Java API. RatMine is a data warehouse that integrates many diverse biological data sets. The main focus is R. norvegicus genomics and proteomics. By integrating such data into one place it is possible to construct queries across domains of biological knowledge. The RatMine user interface is designed to go beyond simply looking up an identifier and viewing a report page. Some of the features include: * Quick Search is available just like on other sites, type in an identifier to see a report page. * Template queries are ''canned'' queries that provide a simple form to perform a specific task. You can create your own templates if you log in. * Lists lets you operate on whole lists of data at once. You can upload lists or save them from results tables. We also create useful public lists for everyone to use. * MyMine lets you create an account to save your own queries, bags and templates, as well as marking public templates as favorites.

Proper citation: RatMine (RRID:SCR_004190) Copy   

•   Source: SciCrunch Registry