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http://bioinfo-out.curie.fr/projects/micsa/

A software package for the identification of transcription factor binding sites in ChIP-Seq data, developed by Computational Systems Biology of Cancer group at the Bioinformatics Laboratory of Institut Curie (Paris).

Proper citation: MICSA (RRID:SCR_010860) Copy   

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http://www.cs.ucr.edu/~polishka/

A command line software tool for accurate placing of the nucleosomes using a Modified Gaussian Mixture Model. It was designed to resolve overlapping nucleosomes and extract extra information (fuzziness, probability, etc.) of nucleosome placement. To achieve this goal the tool clusters the input tags according to Nucleosome Model (see the paper for detailed description) using EM learning process. The tool is written in C++. There are no special requirements except for g++ compiler and *nix environment to compile and use the tool. It was checked to compile using g++ compiler under Ubuntu 11.04 and Mac OS X 10.6

Proper citation: NOrMAL (RRID:SCR_010889) Copy   

•   Source: SciCrunch Registry

https://launchpad.net/asterias

A set of web-based applications for the analysis of genomic and proteomic data. Asterias combines Python with R and C/C++, using MPI for parallelization, and aspires to become a standard for high-performance, distributed, web-based bioinformatics and biostatistics applications.

Proper citation: Asterias (RRID:SCR_010936) Copy   

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http://chipster.csc.fi/

A user-friendly analysis software for high-throughput data.

Proper citation: Chipster (RRID:SCR_010939) Copy   

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http://methmarker.mpi-inf.mpg.de/

Tool that facilitates the design and optimization of gene-specific DNA methylation assays. Beyond its use as an epigenetic primer-design tool, it provides extensive support for epigenetic biomarker optimization. Download MethMarker or start it directly from within your web browser.

Proper citation: MethMarker (RRID:SCR_010908) Copy   

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http://sissrs.rajajothi.com/

Anl algorithm for precise identification of binding sites from short reads generated from ChIP-Seq experiments.

Proper citation: SISSRs (RRID:SCR_010866) Copy   

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http://code.google.com/p/zinba/

Software to identify genomic regions enriched in a variety of ChIP-seq and related next-generation sequencing experiments (DNA-seq), calling both broad and narrow modes of enrichment across a range of signal-to-noise ratios. ZINBA models and accounts for factors that co-vary with background or experimental signal, such as G/C content, and identifies enrichment in genomes with complex local copy number variations. ZINBA provides a single unified framework for analyzing DNA-seq experiments in challenging genomic contexts.

Proper citation: ZINBA (RRID:SCR_010868) Copy   

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http://aroma-project.org/

An R package for analyzing large Affymetrix data sets.

Proper citation: Aroma.affymetrix (RRID:SCR_010919) Copy   

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http://bioinfo.au.tsinghua.edu.cn/software/NURD/

An algorithm to inference isoform expression., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: NURD (RRID:SCR_010988) Copy   

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http://mocklerlab.org/tools/1

An application for discovering potential splice junctions in high throughput sequencing (HTS) data.

Proper citation: Supersplat (RRID:SCR_009826) Copy   

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http://www.biochem.ucl.ac.uk/bsm/virus_database/VIDA3/VIDA.html

VIDA contains a collection of homologous protein families derived from open reading frames from complete and partial virus genomes. For each family, users can get an alignment of the conserved regions, functional and taxonomy information, and links to DNA sequences and structures. * Search homologous protein families from particular virus families * Links to complete genome sequence: Arteriviridae, Coronaviridae, Herpesviridae, Poxviridae The Virus Database at University College London has been developed as a system to organize animal virus open reading frame sequences. All known and predicted protein sequences from complete and partial genomes of particular virus families are extracted from GenBank and filtered to remove 100% redundancy. On the basis of sequence similarity the sequences are then clustered into homologous protein families (HPFs). The families are enriched with annotations including function and functional classification, related protein structures, taxonomy, length of the proteins, boundaries of the conserved region/s, virus-specific gene name and links to EMBL entries and SWISSPROT., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: VIDA (RRID:SCR_007111) Copy   

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https://www.integromics.com/omicsoffice-for-ngs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 18,2025. Software for secondary and tertiary analysis of Next Generation Sequencing (NGS) data.

Proper citation: OmicsOffice for NGS SeqSolve (RRID:SCR_001222) Copy   

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http://www.bioinfor.com/zoom/general/overview.html

Software to map the Illumina/Solexa reads of 15x coverage of a human genome to the reference human genome in one CPU-day, allowing two mismatches, at full sensitivity.

Proper citation: ZOOM (RRID:SCR_002175) Copy   

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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   

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https://github.com/Gaius-Augustus/BRAKER

Software tool as pipeline for accurate and automated gene prediction in novel eukaryotic genomes. Automated gene prediction training and gene prediction pipeline.BRAKER1 is eukaryotic genome annotation pipeline. BRAKER2 is extension of BRAKER1 which allows for fully automated training of gene prediction tools GeneMark EX R14, R15, R17, F1 and AUGUSTUS from RNA Seq and/or protein homology information, and that integrates extrinsic evidence from RNA-Seq and protein homology information into prediction.

Proper citation: BRAKER (RRID:SCR_018964) Copy   

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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   

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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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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

http://purl.bioontology.org/ontology/IMGT-ONTOLOGY

Ontology for immunogenetics and immunoinformatics. Provides semantic specification of terms to be used in immunogenetics and immunoinformatics and manages related knowledge, thus allowing standardization for immunogenetics data from genome, proteome, genetics, two-dimensional (2D) and three-dimensional (3D) structures. Manages the knowledge through diverse facets relying on seven axioms, IDENTIFICATION, CLASSIFICATION, DESCRIPTION, NUMEROTATION, LOCALIZATION, ORIENTATION and OBTENTION. These axioms postulate that any object, any process and any relation can be identified, classified, described, numbered, localized and orientated, and the way it is obtained can be characterized. The axioms constitute the Formal IMGT-ONTOLOGY, also designated as IMGT-Kaleidoscope. As the same axioms can be used to generate concepts for multi-scale level approaches, the Formal IMGT-ONTOLOGY represents a paradigm for system biology ontologies, which need to identify, to classify, to describe, to number, to localize and to orientate objects, processes and relations at the molecule, cell, tissue, organ, organism or population levels. IMGT, the international ImMunoGeneTics information system, has been built on IMGT-ONTOLOGY. The version 1.0.2 of IMGT-ONTOLOGY includes the concepts of IDENTIFICATION and the concepts of CLASSIFICATION.

Proper citation: IMGT-ONTOLOGY (RRID:SCR_010342) 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