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https://github.com/compbiolabucf/PTNet

Graph based learning model for protein expression estimation by considering miRNA-mRNA interactions. Estimates protein levels by considering miRNA-mRNA interaction network, mRNA expression and miRNA expression.

Proper citation: PTNet (RRID:SCR_022975) Copy   

•   Source: SciCrunch Registry

https://github.com/caraweisman/abSENSE

Software to interpret undetected homolog.Method that calculates probability that homolog of given gene would fail to be detected by homology search in given species, even if homolog were present and evolving normally.

Proper citation: abSENSE (RRID:SCR_023223) Copy   

•   Source: SciCrunch Registry

https://github.com/DeNardoLab/BehaviorDEPOT

Software tool for automated behavioral detection based on markerless pose tracking. Behavioral analysis tool to first compile and clean point-tracking output from DeepLabCut, and then classify behavioral epochs using custom behavior classifiers. Used to detect frame by frame behavior from video time series and can analyze results of common experimental assays, including fear conditioning, decision-making in T-maze, open field, elevated plus maze, and novel object exploration. Calculates kinematic and postural statistics from keypoint tracking data from pose estimation software outputs.

Proper citation: BehaviorDEPOT (RRID:SCR_023602) Copy   

•   Source: SciCrunch Registry

https://github.com/SlicerMorph/SlicerMorph

Open and extensible platform to retrieve, visualize and analyse 3D morphology.Extension to import microCT data and conduct 3D morphometrics in Slicer. Used for data import, visualization, measurement, annotation, and geometric morphometric analysis on 3D data, including volumetric scans (CTs and MRs) and 3D surface scans, all within the 3D Slicer application.

Proper citation: SlicerMorph (RRID:SCR_024674) Copy   

•   Source: SciCrunch Registry

https://github.com/compgenomics/MeTPeak

Software package for finding the location of m6A sites in MeRIP-seq data.

Proper citation: MeTPeak (RRID:SCR_026533) Copy   

•   Source: SciCrunch Registry

https://github.com/YuningHao/FARDEEP

Software R tool for enumerating immune cell subsets from whole tumor tissue samples. Utilizes adaptive least trimmed square to automatically detect and remove outliers before estimating cell compositions.

Proper citation: FARDEEP (RRID:SCR_026704) Copy   

•   Source: SciCrunch Registry

https://github.com/DerrickWood/kraken2

Software tool as second version of Kraken taxonomic sequence classification system.

Proper citation: kraken2 (RRID:SCR_026838) Copy   

•   Source: SciCrunch Registry

https://github.com/KrishnaswamyLab/PHATE

Software tool for visualizing high dimensional data using novel conceptual framework for learning and visualizing manifold to preserve both local and global distances.

Proper citation: PHATE (RRID:SCR_027119) Copy   

•   Source: SciCrunch Registry

https://bioinformatics.sdstate.edu/idep/

Integrated web application for differential expression and pathway analysis of RNA-Seq data.

Proper citation: iDEP: Integrated Differential Expression and Pathway analysis (RRID:SCR_027373) Copy   

•   Source: SciCrunch Registry

https://venomsbase-dashboard.shinyapps.io/VenomLanding/

Open-access, browser-based visualization and summary tool for venom transcriptomic and proteomic data. R Shiny–based interactive application designed as visualization and reporting interface for venom transcriptomic and proteomic data. It enables users to explore annotation metrics, toxin gene families, and quality-control summaries generated by analysis pipelines. While it will eventually serve as part of the VenomsBase front end, VenomView currently operates as standalone prototype. Provides interactive dashboards showing assembly quality, annotation scores, toxin gene families, and functional domains generated by the VenomFlow analysis pipeline. Connected to VenomLanding, VenomView currently features Doryteuthis pealeii (Squid), linking metadata with detailed annotation summaries. The expanded version will include Sepia bandensis (Cuttlefish), Octopus bimaculoides, and arachnid species.

Proper citation: VenomView (RRID:SCR_027588) Copy   

•   Source: SciCrunch Registry

https://github.com/McGranahanLab/TcellExTRECT

Software R package to calculate T cell fractions from WES data from hg19 or hg38 aligned genomes.

Proper citation: T Cell ExTRECT (RRID:SCR_027742) Copy   

•   Source: SciCrunch Registry

https://github.com/vanallenlab/comut

Software Python library for creating comutation plots to visualize genomic and phenotypic information. Used for visualizing genomic and phenotypic information via comutation plots.

Proper citation: CoMUT (RRID:SCR_027745) Copy   

•   Source: SciCrunch Registry

https://github.com/pyranges/ncls

Software library for nested containment list data structure for interval overlap queries, like interval tree. It is a static interval-tree that is fast for both construction and lookups.

Proper citation: Nested containment list (RRID:SCR_027849) Copy   

•   Source: SciCrunch Registry

http://organelledb.lsi.umich.edu/

Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.

Proper citation: Organelle DB (RRID:SCR_007837) Copy   

•   Source: SciCrunch Registry

http://www.fgsc.net/

The Fungal Genetics Stock Center is a resource available to the Fungal Genetics research community and to educational and research organizations in general. While some fungi can cause disease in humans, most people have innate immunity against fungi. Some people with diseases of the immune system are at increased risk of infection by fungi. Drugs have been developed in the last 5 years that help with this. Fungal Genetics is the study of genes and genetic traits in fungi. In the past this has been important in the elucidation of what a gene is, what the genetic material is, how genes relate to enzymes, how enzymes relate to traits and how important traits change or evolve. In the present, Fungal Genetics is important to understanding how fungi are pathogens of plants and animals, how fungi can be used in industry for the production of enzymes, chemicals, food, and drugs. Fungi are also essential to processing bio-mass in the attempt to use ethanol as a fuel source. The FGSC is funded largely by a grant from the National Science Foundation (Award Number 0235887) of the United States of America. Sponsors: Supported by a grant from the National Science Foundation.

Proper citation: Fungal Genetics Stock Center (RRID:SCR_008143) Copy   

•   Source: SciCrunch Registry

http://www.poissonboltzmann.org/apbs/

APBS is a software package for modeling biomolecular solvation through solution of the Poisson-Boltzmann equation (PBE), one of the most popular continuum models for describing electrostatic interactions between molecular solutes in salty, aqueous media. APBS was designed to efficiently evaluate electrostatic properties for such simulations for a wide range of length scales to enable the investigation of molecules with tens to millions of atoms. It also provides implicit solvent models of nonpolar solvation which accurately account for both repulsive and attractive solute-solvent interactions. APBS uses FEtk (the Finite Element ToolKit) to solve the Poisson-Boltzmann equation numerically. FEtk is a portable collection of finite element modeling class libraries written in an object-oriented version of C. It is designed to solve general coupled systems of nonlinear partial differential equations using adaptive finite element methods, inexact Newton methods, and algebraic multilevel methods.

Proper citation: Adaptive Poisson-Boltzmann Solver (RRID:SCR_008387) Copy   

•   Source: SciCrunch Registry

http://wiki.c2b2.columbia.edu/honiglab_public/index.php/Software:Jackal

Jackal is a collection of programs designed for the modeling and analysis of protein structures. Its core program is a versatile homology modeling package. It contains twelve individual programs, each with their own function.

Proper citation: Jackal (RRID:SCR_008665) Copy   

•   Source: SciCrunch Registry

http://pslid.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.

Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging.

Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy   

•   Source: SciCrunch Registry

http://iubio.bio.indiana.edu:8089/

Provides summary of gene and genomic information from eukaryotic organism databases. This includes gene symbol and full name, chromosome, genetic and molecular map information, Gene Ontology (Function/Location/Process) and gene homology, product information, links to extended gene information.

Proper citation: Eukaryote Genes (RRID:SCR_008617) Copy   

•   Source: SciCrunch Registry

http://lamp.icsi.berkeley.edu/lamp/

A software package for the inference of locus-specific ancestry in recently admixed populations. LAMP-LD takes the genotypes of admixed individuals as well as reference haplotype panels approximating the mixing ancestral populations, and outputs the estimated number of alleles from each ancestry in each locus for each individual. The LAMP-LD package also includes the program LAMP-HAP, which processes haplotype data when high-quality phasing is available, and utilizes trio nuclear family designs to improve estimation accuracy. LAMP-LD is based on a window-based processing combined within a hierarchical Hidden Markov Model. It can process 2,3 or 5 mixing populations, and its short per-sample processing time makes it suitable for analyzing large datasets of dense SNP panels. The original program LAMP does not use the LD and therefore is not as accurate, but it is useful in cases where the SNP density is not high enough or when the ancestral haplotypes are unkown.

Proper citation: Local Ancestry in adMixed Populations (RRID:SCR_001258) Copy   

•   Source: SciCrunch Registry