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http://www.megabionet.org/atpid/webfile/

Centralized platform to depict and integrate the information pertaining to protein-protein interaction networks, domain architecture, ortholog information and GO annotation in the Arabidopsis thaliana proteome. The Protein-protein interaction pairs are predicted by integrating several methods with the Naive Baysian Classifier. All other related information curated is manually extracted from published literature and other resources from some expert biologists. You are welcomed to upload your PPI or subcellular localization information or report data errors. Arabidopsis proteins is annotated with information (e.g. functional annotation, subcellular localization, tissue-specific expression, phosphorylation information, SNP phenotype and mutant phenotype, etc.) and interaction qualifications (e.g. transcriptional regulation, complex assembly, functional collaboration, etc.) via further literature text mining and integration of other resources. Meanwhile, the related information is vividly displayed to users through a comprehensive and newly developed display and analytical tools. The system allows the construction of tissue-specific interaction networks with display of canonical pathways.

Proper citation: Arabidopsis thaliana Protein Interactome Database (RRID:SCR_001896) Copy   

•   Source: SciCrunch Registry

http://fcon_1000.projects.nitrc.org/indi/CoRR/html/

Consortium that has aggregated resting state fMRI (R-fMRI) and diffusion imaging data from laboratories around the world, creating an open science resource for the imaging community, that facilitates the assessment of test-retest reliability and reproducibility for functional and structural connectomics. Given that this was a retrospective data collection, they have focused on basic phenotypic measures that are relatively standard in the neuroimaging field, as well as fundamental for analyses and sample characterization. Their phenotypic key is organized to reflect three classifications of variables: 1) core (i.e., minimal variables required to characterize any dataset), 2) preferred (i.e., variables that were strongly suggested for inclusion due to their relative import and/or likelihood of being collected by most sites), and 3) optional (variables that are data-set specific or only shared by a few sites). CoRR includes 33 datasets consisting of: * 1629 Subjects * 3357 Anatomical Scans * 5093 Resting Functional Scans * 1302 Diffusion Scans * 300 CBF and ASL Scans

Proper citation: Consortium for Reliability and Reproducibility (RRID:SCR_003774) Copy   

•   Source: SciCrunch Registry

http://hapmap.ncbi.nlm.nih.gov/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. A multi-country collaboration among scientists and funding agencies to develop a public resource where genetic similarities and differences in human beings are identified and catalogued. Using this information, researchers will be able to find genes that affect health, disease, and individual responses to medications and environmental factors. All of the information generated by the Project will be released into the public domain. Their goal is to compare the genetic sequences of different individuals to identify chromosomal regions where genetic variants are shared. Public and private organizations in six countries are participating in the International HapMap Project. Data generated by the Project can be downloaded with minimal constraints. HapMap project related data, software, and documentation include: bulk data on genotypes, frequencies, LD data, phasing data, allocated SNPs, recombination rates and hotspots, SNP assays, Perlegen amplicons, raw data, inferred genotypes, and mitochondrial and chrY haplogroups; Generic Genome Browser software; protocols and information on assay design, genotyping and other protocols used in the project; and documentation of samples/individuals and the XML format used in the project.

Proper citation: International HapMap Project (RRID:SCR_002846) Copy   

•   Source: SciCrunch Registry

http://idm.fudan.edu.cn/PBmice/

Database for storing, retrieving, and displaying the information derived from piggyBac (PB) insertions (Insert) and their characterizations in the mouse genome with piggyBac transposon system. Quick Search and Advanced Search tools have been provided to find information in the PBmice database, the result is centered on Inserts and provides information related to the Inserts. A mapping database is linked to PBmice too. This mapping database allows row experiment data to be inputted in. All the mature data can be allowed publish to PBmice. PBmice Source Code is available with a License Agreement.

Proper citation: PBmice (RRID:SCR_006978) Copy   

•   Source: SciCrunch Registry

http://medblast.sibsnet.org/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. An algorithm that finds articles most relevant to a genetic sequence. In the genomic era, researchers often want to know more information about a biological sequence by retrieving its related articles. However, there is no available tool yet to achieve conveniently this goal. Here, a new literature-mining tool MedBlast is developed, which uses natural language processing techniques, to retrieve the related articles of a given sequence. An online server of this program is also provided. The genome sequencing projects generate such a large amount of data every day that many molecular biologists often encounter some sequences that they know nothing about. Literature is usually the principal resource of such information. It is relatively easy to mine the articles cited by the sequence annotation; however, it is a difficult task to retrieve those relevant articles without direct citation relationship. The related articles are those described in the given sequence (gene/protein), or its redundant sequences, or the close homologs in various species. They can be divided into two classes: direct references, which include those either cited by the sequence annotation or citing the sequence in its text; indirect references, those which contain gene symbols of the given sequence. A few additional issues make the task even more complicated: (1) symbols may have aliases; and (2) one sequence may have a couple of relatives that we want to take into account too, which include redundant (e.g. protein and gene sequences) and close homologs. Here the issues are addressed by the development of the software MedBlast, which can retrieve the related articles of the given sequence automatically. MedBlast uses BLAST to extend homology relationships, precompiled species-specific thesauruses, a useful semantics technique in natural language processing (NLP), to extend alias relationship, and EUtilities toolset to search and retrieve corresponding articles of each sequence from PubMed. MedBlast take a sequence in FASTA format as input. The program first uses BLAST to search the GenBank nucleic acid and protein non-redundant (nr) databases, to extend to those homologous and corresponding nucleic acid and protein sequences. Users can input the BLAST results directly, but it is recommended to input the result of both protein and nucleic acid nr databases. The hits with low e-values are chosen as the relatives because the low similarity hits often do not contain specific information. Very long sequences, e.g. 100k, which are usually genomic sequences, are discarded too, for they do not contain specific direct references. User can adjust these parameters to meet their own needs.

Proper citation: MedBlast (RRID:SCR_008202) Copy   

•   Source: SciCrunch Registry

https://github.com/YangLab/CLEAR

Software tool as computational pipeline for circular and linear RNA expression analysis from ribosomal-RNA depleted RNA-seq. CIRCexplorer3-CLEAR is CLEAR pipeline for direct comparison of circular and linear RNA expression.

Proper citation: CLEAR (RRID:SCR_021663) Copy   

•   Source: SciCrunch Registry

http://www.immunoinformatics.net/HLAsupE/

Database of HLA supertype-specific epitopes. It describes major histocompatibility complex (MHC) molecules that bind short peptides derived from endogenous or exogenous antigens and present them onto the surface of antigen-presenting cells (APCs) for T-cell receptor (TCR) recognition.

Proper citation: HLAsupE (RRID:SCR_016277) Copy   

•   Source: SciCrunch Registry

http://bio-bigdata.hrbmu.edu.cn/lnc2cancer/

Manually curated database of experimentally supported lncRNAs associated with various human cancers. Cancer long non coding RNA database. Lnc2Cancer 3.0 is updated resource for experimentally supported lncRNA/circRNA cancer associations and web tools based on RNA-seq and scRNA-seq data.

Proper citation: lnc2cancer (RRID:SCR_023781) Copy   

•   Source: SciCrunch Registry

http://datf.cbi.pku.edu.cn/

Database that collects all arabidopsis transcription factors (totally 1922 Loci; 2290 Gene Models) and classifies them into 64 families. It uses not only locus (gene), but also gene model (transcript, protein) and the detail information is for each gene model not for locus. It adds multiple alignment of the DNA-binding domain of each family, Neighbor-Joining phylogenetic tree of each family, the GO annotation, homolog with the Database of Rice Transcription Factors (DRTF). It also keeps old information items such as the unique cloned and sequenced information of about 1200 transcription factors, protein domains, 3D structure information with BLAST hits against PDB, predicted Nuclear Location Signals, UniGene information, as well as links to literature reference.

Proper citation: Database of Arabidopsis Transcription Factors (RRID:SCR_007101) Copy   

•   Source: SciCrunch Registry

http://wego.genomics.org.cn/cgi-bin/wego/index.pl

Web Gene Ontology Annotation Plot (WEGO) is a simple but useful tool for plotting Gene Ontology (GO) annotation results. Different from other commercial software for chart creating, WEGO is designed to deal with the directed acyclic graph (DAG) structure of GO to facilitate histogram creation of GO annotation results. WEGO has been widely used in many important biological research projects, such as the rice genome project and the silkworm genome project. It has become one of the useful tools for downstream gene annotation analysis, especially when performing comparative genomics tasks. Platform: Online tool

Proper citation: WEGO - Web Gene Ontology Annotation Plot (RRID:SCR_005827) Copy   

•   Source: SciCrunch Registry

https://github.com/basehc/IPEV

Software tool to identify of Prokaryotic and Eukaryotic virus derived sequences in virome using deep learning. Used to calculate set of scores that reflect probability that input sequence fragments are prokaryotic and eukaryotic viral sequences.

Proper citation: IPEV (RRID:SCR_023702) Copy   

•   Source: SciCrunch Registry

http://www.lirmed.com/tam2/

Web server for miRNA set enrichment analysis. TAM 2.0 is updated version of this web server. Allows to test functional and disease annotations of miRNAs by overrepresentation analysis and to compare input de-regulated miRNAs with those de-regulated in other disease conditions via correlation analysis.

Proper citation: TAM (RRID:SCR_023800) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/miRBaseConverter/

Software R package for converting and retrieving information of miRNAs in different miRBase versions. Used for converting and retrieving miRNA Name, Accession, Sequence, Version, History and Family information in different miRBase versions. Can process huge number of miRNAs in short time without other depends.

Proper citation: miRBaseConverter (RRID:SCR_023873) Copy   

•   Source: SciCrunch Registry

http://www.rna-society.org/rnalocate/

Web tool for RNA subcellular localizations analysis. RNALocate v2.0 is updated resource for RNA subcellular localization with increased coverage and annotation.

Proper citation: RNALocate (RRID:SCR_024418) Copy   

•   Source: SciCrunch Registry

http://huanglab.phys.hust.edu.cn/hpepdock/

Web server for blind peptide protein docking based on hierarchical algorithm. Blind peptide-protein docking by fast modeling of peptide conformations and global sampling of binding orientations.

Proper citation: HPEPDOCK Server (RRID:SCR_018561) Copy   

•   Source: SciCrunch Registry

https://github.com/BGI-shenzhen/PopLDdecay

Software tool for linkage disequilibrium decay analysis based on variant call format files.

Proper citation: PopLDdecay (RRID:SCR_022509) Copy   

•   Source: SciCrunch Registry

http://lilab-ecust.cn/pharmmapper/index.html

Web server for potential drug target identification using pharmacophore mapping approach.Designed to identify potential target candidates for given probe small molecules including drugs, natural products, or other newly discovered compounds with binding targets unidentified using pharmacophore mapping approach. Used for potential drug target identification with comprehensive target pharmacophore database.

Proper citation: PharmMapper (RRID:SCR_022604) Copy   

•   Source: SciCrunch Registry

http://easybioai.com/sc2disease/

Manually curated database of single cell transcriptome for human diseases. scRNA-seq database derived from numerous human studies. Provides researchers with encyclopedia of biomarkers at level of genes, cells, and diseases.

Proper citation: SC2diseases (RRID:SCR_019093) Copy   

•   Source: SciCrunch Registry

https://sourceforge.net/projects/metabarcoding/

Software for metabarcoding of DNA. SOAPBarcode takes advantage of high throughput capacity of next-generation-sequencing (NGS) platforms and can characterize the biodiversity of large volumes of eukaryote samples.

Proper citation: SOAPBarcode (RRID:SCR_015776) Copy   

•   Source: SciCrunch Registry

http://www.bioinfo.org.cn/hptaa/

To accelerate the process of tumor antigen discovery, we generated a publicly available Human Potential Tumor Associated Antigen database (HPtaa) with pTAAs identified by insilico computing. 3518 potential targets have been included in the database, which is freely available to academic users. It successfully screened out 41 of 82 known Cancer-Testis antigens, 6 of 18 differentiation antigen, 2 of 2 oncofetal antigen, and 7 of 12 FDA approved cancer markers that have Gene ID, therefore will provide a good platform for identification of cancer target genes. This database utilizes expression data from various expression platforms, including carefully chosen publicly available microarray expression data, GEO SAGE data, Unigene expression data. In addition, other relevant databases required for TAA discovery such as CGAP, CCDS, gene ontology database etc, were also incorporated. In order to integrate different expression platforms together, various strategies and algorithms have been developed. Known tumor antigens are gathered from literature and serve as training sets. A total tumor specificity penalty was computed from positive clue penalty for differential expression in human cancers, the corresponding differential ratio, and normal tissue restriction penalty for each gene. We hope this database will help with the process of cancer immunome identification, thus help with improving the diagnosis and treatment of human carcinomas.

Proper citation: Human Potential Tumor Associated Antigen database (RRID:SCR_002938) Copy   

•   Source: SciCrunch Registry