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http://www.jcvi.org/charprotdb/index.cgi/home

The Characterized Protein Database, CharProtDB, is designed and being developed as a resource of expertly curated, experimentally characterized proteins described in published literature. For each protein record in CharProtDB, storage of several data types is supported. It includes functional annotation (several instances of protein names and gene symbols) taxonomic classification, literature links, specific Gene Ontology (GO) terms and GO evidence codes, EC (Enzyme Commisssion) and TC (Transport Classification) numbers and protein sequence. Additionally, each protein record is associated with cross links to all public accessions in major protein databases as ��synonymous accessions��. Each of the above data types can be linked to as many literature references as possible. Every CharProtDB entry requires minimum data types to be furnished. They are protein name, GO terms and supporting reference(s) associated to GO evidence codes. Annotating using the GO system is of importance for several reasons; the GO system captures defined concepts (the GO terms) with unique ids, which can be attached to specific genes and the three controlled vocabularies of the GO allow for the capture of much more annotation information than is traditionally captured in protein common names, including, for example, not just the function of the protein, but its location as well. GO evidence codes implemented in CharProtDB directly correlate with the GO consortium definitions of experimental codes. CharProtDB tools link characterization data from multiple input streams through synonymous accessions or direct sequence identity. CharProtDB can represent multiple characterizations of the same protein, with proper attribution and links to database sources. Users can use a variety of search terms including protein name, gene symbol, EC number, organism name, accessions or any text to search the database. Following the search, a display page lists all the proteins that match the search term. Click on the protein name to view more detailed annotated information for each protein. Additionally, each protein record can be annotated.

Proper citation: CharProtDB: Characterized Protein Database (RRID:SCR_005872) Copy   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/mammals/haploreg/haploreg.php

HaploReg is a tool for exploring annotations of the noncoding genome at variants on haplotype blocks, such as candidate regulatory SNPs at disease-associated loci. Using linkage disequilibrium (LD) information from the 1000 Genomes Project, linked SNPs and small indels can be visualized along with their predicted chromatin state in nine cell types, conservation across mammals, and their effect on regulatory motifs. HaploReg is designed for researchers developing mechanistic hypotheses of the impact of non-coding variants on clinical phenotypes and normal variation.

Proper citation: HaploReg (RRID:SCR_006796) Copy   

•   Source: SciCrunch Registry

http://www.uniprot.org/help/uniref

Databases which provide clustered sets of sequences from UniProt Knowledgebase and selected UniParc records, in order to obtain complete coverage of sequence space at several resolutions while hiding redundant sequences from view. The UniRef100 database combines identical sequences and sub-fragments with 11 or more residues (from any organism) into a single UniRef entry. The sequence of a representative protein, the accession numbers of all the merged entries, and links to the corresponding UniProtKB and UniParc records are all displayed in the entry. UniRef90 and UniRef50 are built by clustering UniRef100 sequences with 11 or more residues such that each cluster is composed of sequences that have at least 90% (UniRef90) or 50% (UniRef50) sequence identity to the longest sequence (UniRef seed sequence). All the sequences in each cluster are ranked to facilitate the selection of a representative sequence for the cluster.

Proper citation: UniRef (RRID:SCR_010646) Copy   

•   Source: SciCrunch Registry

http://www.informatics.jax.org/

Community model organism database for laboratory mouse and authoritative source for phenotype and functional annotations of mouse genes. MGD includes complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics.Contains standardized descriptions of mouse phenotypes, associations between mouse models and human genetic diseases, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information. Data are obtained and integrated via manual curation of the biomedical literature, direct contributions from individual investigators and downloads from major informatics resource centers. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology.

Proper citation: Mouse Genome Database (RRID:SCR_012953) Copy   

•   Source: SciCrunch Registry

http://hb.flatironinstitute.org/

Formerly known as GIANT (Genome-scale Integrated Analysis of gene Networks in Tissues), HumanBase applies machine learning algorithms to learn biological associations from massive genomic data collections. These integrative analyses reach beyond existing "biological knowledge" represented in the literature to identify novel, data-driven associations.

Proper citation: HumanBase (RRID:SCR_016145) Copy   

•   Source: SciCrunch Registry

https://phenodb.org/

Database for phenotype genotype associations for humans. Used by clinical researchers to store standardized phenotypic information, diagnosis, and pedigree data and then run analyses on VCF files from individuals, families or cohorts with suspected Mendelian disease.

Proper citation: PhenoDB (RRID:SCR_016551) Copy   

•   Source: SciCrunch Registry

https://dfam.org/home

Open collection of Transposable Element DNA sequence alignments, hidden Markov Models, consensus sequences, and genome annotations.Dfam 3.2 provides early access to uncurated, de novo generated families.

Proper citation: Dfam (RRID:SCR_021168) Copy   

•   Source: SciCrunch Registry

http://pgfe.umassmed.edu/ffs/

Database of Drosophila transcription factor DNA binding specificity using the bacterial one-hybrid method, DNase I or SELEX methods. The database provides community access to recognition motifs and position weight matrices for transcription factors (TFs), including many unpublished motifs. Search tools and flat file downloads are provided to retrieve binding site information (as sequences, matrices and sequence logos) for individual TFs, groups of TFs or for all TFs with characterized binding specificities. Linked analysis tools allow users to identify motifs within the database that share similarity to a query matrix or to view the distribution of occurrences of an individual motif throughout the Drosophila genome. This database and its associated tools provide computational and experimental biologists with resources to predict interactions between Drosophila TFs and target cis-regulatory sequences.

Proper citation: FlyFactorSurvey (RRID:SCR_002113) Copy   

•   Source: SciCrunch Registry

http://zfin.org

Model organism database that serves as central repository and web-based resource for zebrafish genetic, genomic, phenotypic and developmental data. Data represented are derived from three primary sources: curation of zebrafish publications, individual research laboratories and collaborations with bioinformatics organizations. Data formats include text, images and graphical representations.Serves as primary community database resource for laboratory use of zebrafish. Developed and supports integrated zebrafish genetic, genomic, developmental and physiological information and link this information extensively to corresponding data in other model organism and human databases.

Proper citation: Zebrafish Information Network (ZFIN) (RRID:SCR_002560) Copy   

•   Source: SciCrunch Registry

https://github.com/marbl/salsa

Software tool for scaffold long read assemblies with Hi-C data.

Proper citation: SALSA (RRID:SCR_022013) Copy   

•   Source: SciCrunch Registry

https://www.hsph.harvard.edu/alkes-price/software/

Software application that uses genotyping data from SNP arrays for accurately inferring chromosomal segments of distinct continental ancestry in admixed populations, using dense genetic data. (entry from Genetic Analysis Software)

Proper citation: Hapmix (RRID:SCR_004203) Copy   

•   Source: SciCrunch Registry

https://github.com/greenelab/miQC

Software tool as flexible, probablistic metrics for quality control of scRNA-seq data. Adaptive probabilistic framework for quality control of single-cell RNA-sequencing data. Data driven QC metric that jointly models proportion of reads mapping to mtDNA and number of detected genes with mixture models in probabilistic framework to predict which cells are low quality in given dataset.

Proper citation: miQC (RRID:SCR_022697) Copy   

•   Source: SciCrunch Registry

http://clovr.org/

A desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing.

Proper citation: CloVR (RRID:SCR_005290) Copy   

•   Source: SciCrunch Registry

http://zfishbook.org/

Collection of revertible protein trap gene-breaking transposon (GBT) insertional mutants in zebrafish with active or cryopreserved lines from initially identified lines. Open to community-wide contributions including expression and functional annotation and represents world-wide central hub for information on how to obtain these lines from diverse members of International Zebrafish Protein Trap Consortium (IZPTC) and integration within other zebrafish community databases including Zebrafish Information Network (ZFIN), Ensembl and National Center for Biotechnology Information. Registration allows users to save their favorite lines for easy access, request lines from Mayo Clinic catalog, contribute to line annotation with appropriate credit, and puts them on optional mailing list for future zfishbook newletters and updates.

Proper citation: zfishbook (RRID:SCR_006896) Copy   

•   Source: SciCrunch Registry

http://hanalyzer.sourceforge.net/

An open-source data integration system designed to assist biologists in explaining the results observed in genome-scale experiments as well as generating new hypotheses. It combines information extraction techniques, semantic data integration, and reasoning and facilitates network visualization. The Hanalyzer source code and binaries are available for download.

Proper citation: Hanalyzer (RRID:SCR_000923) Copy   

•   Source: SciCrunch Registry

https://github.com/hms-dbmi/spp

R analysis and processing package for Illumina platform Chip-Seq data.

Proper citation: SPP (RRID:SCR_001790) Copy   

•   Source: SciCrunch Registry

http://research.mssm.edu/integrative-network-biology/Software.html

Software tool as probabilistic multi omics data matching procedure to curate data, identify and correct data annotation and errors in large databases. Used to check potential labeling errors in profiles where number of cis relationships is small, such as miRNA and RPPA profiles.

Proper citation: proMODMatcher (RRID:SCR_017219) Copy   

•   Source: SciCrunch Registry

https://github.com/aidenlab/juicer.git

Software platform for analyzing kilobase resolution Hi-C data. Open source tool for analyzing terabase scale Hi-C datasets. Allowes to transform raw sequence data into normalized contact maps.

Proper citation: Juicer (RRID:SCR_017226) Copy   

•   Source: SciCrunch Registry

http://topaz.gatech.edu/GeneMark/

Software package for ab initio identification of protein coding regions in RNA transcripts. Algorithm parameters are estimated by unsupervised training which makes unnecessary manually curated preparation of training sets. Sets of assembled eukaryotic transcripts can be analyzed by modified GeneMarkS-T algorithm which part of gene prediction programs GeneMark.

Proper citation: GeneMarkS-T (RRID:SCR_017648) Copy   

•   Source: SciCrunch Registry

https://github.com/macs3-project/MACS

Software Python package for identifying transcript factor binding sites. Used to evaluate significance of enriched ChIP regions. Improves spatial resolution of binding sites through combining information of both sequencing tag position and orientation. Can be used for ChIP-Seq data alone, or with control sample with increase of specificity.

Proper citation: MACS (RRID:SCR_013291) Copy   

•   Source: SciCrunch Registry