Tools   Select Another Resource Report Type

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

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://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

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

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://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://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://ahd.cbi.pku.edu.cn

Database providing a systematic and comprehensive view of morphological phenotypes regulated by plant hormones, as well as regulatory genes participating in numerous plant hormone responses. By integrating the data from mutant studies, transgenic analysis and gene ontology annotation, genes related to the stimulus of eight plant hormones were identified, including abscisic acid, auxin, brassinosteroid, cytokinin, ethylene, gibberellin, jasmonic acid and salicylic acid. Another pronounced characteristics of this database is that a phenotype ontology was developed to precisely describe all kinds of morphological processes regulated by plant hormones with standardized vocabularies. To increase the coverage of phytohormone related genes, the database has been updated from AHD to AHD2.0 adding and integrating several pronounced features: (1) added 291 newly published Arabidopsis hormone related genes as well as corrected information (e.g. the arguable ABA receptors) based on the recent 2-year literature; (2) integrated orthologues of sequenced plants in OrthoMCLDB into each gene in the database; (3) integrated predicted miRNA splicing site in each gene in the database; (4) provided genetic relationship of these phytohormone related genes mining from literature, which represents the first effort to construct a relatively comprehensive and complex network of hormone related genes as shown in the home page of our database; (5) In convenience to in-time bioinformatics analysis, they also provided links to a powerful online analysis platform Weblab that they have recently developed, which will allow users to readily perform various sequence analysis with these phytohormone related genes retrieved from AHD2.0; (6) provided links to other protein databases as well as more expression profiling information that would facilitate users for a more systematic analysis related to phytohormone research. Please help to improve the database with your contributions.

Proper citation: Arabidopsis Hormone Database (RRID:SCR_001792) 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

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.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://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

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

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://www.nitrc.org/projects/gig-ica/

Software toolbox for group-information guided Independent Component Analysis (ICA). In GIG-ICA, group information captured by standard Independent Component Analysis (ICA) on the group level is used as guidance to compute individual subject specific Independent Components (ICs) using a multi-objective optimization strategy. For computing subject specific ICs, GIG-ICA is applicable to subjects that are involved or not involved in the computation of the group information. Besides the group ICs, group information captured from other imaging modalities and meta analysis could be used as the guidance in GIG-ICA too.

Proper citation: Group Information Guided ICA (RRID:SCR_009491) Copy   

•   Source: SciCrunch Registry

http://www.picb.ac.cn/hanlab/iNPS.html

Software for nucleosome detection that builds on the NPS software. Its application to T-cell activation data demonstrates a greater ability to facilitate detection of nucleosome repositioning, uncovering additional biological features underlying the activation process., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: iNPS (RRID:SCR_015750) 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