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http://gst.tennessee.edu/

Graduate School of Genome Science and Technology (GST) is a Life Science graduate program founded on two premises. First, whole-genome sequences and related large-scale datasets have transformed how we perform biological research, a trend that is gathering momentum and is anticipated to frame the way the biology research is accomplished for many years to come. Second, advances in technology, whether at the level of instrumentation, computation, or wet lab reagents, have long been a powerful driving force in biology. The GST program is home to faculty mentors from many walks of life. The virulence factors of pathogenic fungi and the engineering of photosynthetic reaction complexes for bioenergy harvesting are just two examples from the cornucopia of research projects being pursued in GST.

Proper citation: University of Tennessee Genome Science and Technology Graduate Program (RRID:SCR_000038) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/rnaseqvariantbl/

Open source software tool that simulates experimental RNA-seq and DNA whole exome sequences derived from reference genome, aligns these sequences by custom parameters, detects variants and outputs blacklist of positions and alleles caused by mismapping. Used to characterize mappability of RNA-Seq reads and create blacklist of genomic positions of mismapped reads. This blacklist is used to filter potential false positives from variant or RNA editing calls.

Proper citation: BlackOPs (RRID:SCR_000032) Copy   

•   Source: SciCrunch Registry

http://sw-tools.pdb.org/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Information Portal to Biological Macromolecular Structures provides variety of software tools made available through the RCSB. These tools include: data extraction and deposition preparation tools, data format conversion and validation tools, data parsing tools, dictionary and data management tools, visualization tools that support PDBx/mmCIF, and other PDBx/mmCIF software library tools.

Proper citation: RCSB PDB Software Tools (RRID:SCR_000035) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/data/annotation/html/RmiR.Hs.miRNA.html

Software package for various databases of microRNA Targets.

Proper citation: RmiR.Hs.miRNA (RRID:SCR_000101) Copy   

•   Source: SciCrunch Registry

http://www.genetex.com/

An antibody supplier for the purposes of life science and biomedical research. This company has a wide variety of immunological reagents that focus on areas of research such as cancer, cell biology, epigenetics, immunology and infectious diseases.

Proper citation: GeneTex (RRID:SCR_000069) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/nfuse/

Software that predicts fusion transcripts and associated CGRs from matched RNA-seq and Whole Genome Shotgun Sequencing (WGSS).

Proper citation: nFuse (RRID:SCR_000066) Copy   

•   Source: SciCrunch Registry

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

Software tool for identifying structural variants (SVs) from paired-end sequencing data.GASV distribution includes three components that are typically run in succession: the BAM file of unique paired-read mappings is processed; structural variants are identified by clustering discordant fragments; and a probabilistic algorithm improves the specificity of GASV predictions.

Proper citation: GASV (RRID:SCR_000061) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/chipmeta/

Software using a Hierarchical hidden Markov model for jointly analyzing ChIP-chip and ChIP-seq datasets.

Proper citation: ChIPmeta (RRID:SCR_000054) Copy   

•   Source: SciCrunch Registry

https://github.com/SciLifeLab/facs

Software for classification of Sequences using Bloom filters that can accurately and rapidly align sequences to a reference sequence.

Proper citation: FACS (RRID:SCR_000055) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/batman-seq/

A fast BWT-based short reads mapping tools which uses additional statistical method to model error profile of the sequencing experiment.

Proper citation: Batman-Seq (RRID:SCR_000048) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/cancer/cga/indelocator

A software tool for calling short indels in next generation sequencing data.

Proper citation: Indelocator (RRID:SCR_005258) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.knowledgeblog.org/

Series of tutorial material covering a broad selection of topics in bioinformatics. Categories include: Bioinformatics APIs, Data integration, Events, Grid and Cloud Computing, Metabolic modelling, Reviews, Software Comparisons, Statistics, Systems Biology, Transcriptomics, Tutorials.

Proper citation: Bioinformatics Knowledgeblog (RRID:SCR_005379) Copy   

•   Source: SciCrunch Registry

http://compbio.cs.brown.edu/projects/gasv/

Software tool combining both paired read and read depth signals into probabilistic model which can analyze multiple alignments of reads. Used to find structural variation in both normal and cancer genomes using data from variety of next-generation sequencing platforms. Used to predict structural variants directly from aligned reads in SAM/BAM format.Combines read depth information along with discordant paired read mappings into single probabilistic model two common signals of structural variation. When multiple alignments of read are given, GASVPro utilizes Markov Chain Monte Carlo procedure to sample over the space of possible alignments.

Proper citation: GASVPro (RRID:SCR_005259) Copy   

•   Source: SciCrunch Registry

http://bejerano.stanford.edu/prism/public/html/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: PRISM (Stanford database) (RRID:SCR_005375) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/knime4bio/

A set of custom nodes for the KNIME (The Konstanz Information Miner) graphical workbench, for analysing next-generation sequencing (NGS) data without the requirement of programming skills.

Proper citation: Knime4Bio (RRID:SCR_005376) Copy   

•   Source: SciCrunch Registry

http://ergatis.sourceforge.net/

A web interface and scalable software system for bioinformatics workflows that is used to create, run, and monitor reusable computational analysis pipelines. It contains pre-built components for common bioinformatics analysis tasks. These components can be arranged graphically to form highly-configurable pipelines. Each analysis component supports multiple output formats, including the Bioinformatic Sequence Markup Language (BSML). The current implementation includes support for data loading into project databases following the CHADO schema, a highly normalized, community-supported schema for storage of biological annotation data. Ergatis uses the Workflow engine to process its work on a compute grid. Workflow provides an XML language and processing engine for specifying the steps of a computational pipeline. It provides detailed execution status and logging for process auditing, facilitates error recovery from point of failure, and is highly scalable with support for distributed computing environments. The XML format employed enables commands to be run serially, in parallel, and in any combination or nesting level.

Proper citation: Ergatis (RRID:SCR_005377) Copy   

•   Source: SciCrunch Registry

http://toolshed.g2.bx.psu.edu/repository/display_tool?repository_id=5d0de444b1f9ac52&tool_config=database%2Fcommunity_files%2F000%2Frepo_136%2Fcrest.xml&changeset_revision=4f6952e0af48

An algorithm for detecting genomic structural variations at base-pair resolution using next-generation sequencing data. CREST uses pieces of DNA called soft clips to find structural variations. Soft clips are the DNA segments produced during sequencing that fail to properly align to the reference genome as the sample genome is reassembled. CREST uses the soft clips to precisely identify sites of chromosomal rearrangement or where pieces of DNA are inserted or deleted.

Proper citation: CREST (RRID:SCR_005257) Copy   

•   Source: SciCrunch Registry

https://www.har.mrc.ac.uk/about/mammalian-genetics-unit

It is now widely known that animals share many genes with humans and can suffer from the same diseases, for example diabetes or deafness. Investigating these diseases in animals can provide vital leads to understanding both their causes and ways to treat them in humans. This approach to medical research lies at the heart of work at the MRC Mammalian Genetics Unit (MGU) at Harwell in Oxfordshire. In 1995 the MRC Radiobiology Unit was reconstituted to form two new units, the Radiation and Genome Stability Unit and the MGU. These opened in January 1996, together with the UK Mouse Genome Centre which is now part of MGU, making MRC Harwell a unique campus for multi-disciplinary genetics research. Since MGU's Director Steve Brown took the reins in 1996, the unit has dramatically expanded its scientific scope and increased its personnel from 40 to over 100. It now has 13 research programs encompassing molecular genetics, genomics, genetic manipulation and data analysis at all levels, from single genes to the whole genome. With a combination of cutting-edge facilities and expertise unrivaled in Europe, MGU Harwell has become firmly established as one of the world's leading academic centres for mouse genetics.

Proper citation: MRC Mammalian Genetics Unit (RRID:SCR_005378) Copy   

•   Source: SciCrunch Registry

http://mcb.berkeley.edu/labs/werblin/index.html

The goal of our research is to uncover the neural circuitry that mediates some of the remarkable processing capabilities of the retina. The retina to operates at high spatial and temporal resolution over more than 7 orders of magnitude, to detect the direction of motion, to blank and then recover after saccades, to generate at least a dozen different abstract representations of the visual world. How is all of this, and much more, possible in this tissuepaper-thin array of neurons? Videos and images describing this include: * The retinal hypercircuit. * How the Retina Works * Take a Tour through the Retina * Cartoon of the retina showing layering of neurons * Directional Selectivity * Feedback and Crossover inhibition * Multiple Representations of the Visual Scene ** Pseudo Array Recording Methods ** Multiple Representations of the Visual World ** Regions of Frequency Space * Regions of space/time frequency * Space-time rasters for ON and OFF cells * Patching a neuron in a retinal slice * Targeting Retinal Neuron Subregions with Arficial Rhodopsins

Proper citation: Werblin Lab (RRID:SCR_005251) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/molbiolib/

A compact, portable, and extensively tested C++11 software framework and set of applications tailored to the demands of next-generation sequencing data and applicable to many other applications. It is designed to work with common file formats and data types used both in genomic analysis and general data analysis. A central relational-database-like Table class is a flexible and powerful object to intuitively represent and work with a wide variety of tabular datasets, ranging from alignment data to annotations. MolBioLib includes programs to perform a wide variety of analysis tasks such as computing read coverage, annotating genomic intervals, and novel peak calling with a wavelet algorithm. This package assumes fluency in both UNIX and C++.

Proper citation: MolBioLib (RRID:SCR_005372) Copy   

•   Source: SciCrunch Registry