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http://db.phasep.pro/

Provides a collection of manually curated phase separation (PS) proteins and Membraneless organelles (MLOs) related proteins. Annotated phase separation-related proteins with droplet states, co-phase separation partners and other experimental information.

Proper citation: PhaSepDB (RRID:SCR_024964) Copy   

•   Source: SciCrunch Registry

https://rps.renlab.org/#/Home

Comprehensive database of RNAs involved in liquid-liquid phase separation.

Proper citation: RPS (RRID:SCR_024960) Copy   

•   Source: SciCrunch Registry

https://github.com/IOBR/IOBR

Software R package to perform comprehensive analysis of tumor microenvironment and signatures for immuno-oncology. Used for comprehensively interpreting multi-omics data.

Proper citation: IOBR (RRID:SCR_025619) Copy   

•   Source: SciCrunch Registry

https://appyters.maayanlab.cloud/#/hTFtarget_Harmonizome_ETL

Comprehensive database for regulations of Human Transcription Factors and their targets. Provides tools for visualization, interpretation, and analysis of pathway knowledge.

Proper citation: hTFtarget (RRID:SCR_025626) Copy   

•   Source: SciCrunch Registry

https://github.com/nayu0419/stMMR

Software tool for spatial domain identification from spatially resolved transcriptomics with multi-modal feature representation.

Proper citation: stMMR (RRID:SCR_025601) Copy   

•   Source: SciCrunch Registry

https://ngdc.cncb.ac.cn/gsa/

Public archive of raw sequence data in National Genomics Data Center as part of the China National Center for Bioinformation. GSA accepts worldwide data submissions, performs data curation and quality control for all submitted data. Provides data storage and sharing services.

Proper citation: Chinese Genome Sequence Archive (RRID:SCR_025826) Copy   

•   Source: SciCrunch Registry

http://biocc.hrbmu.edu.cn/CancerSEA/

Database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level. Provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single-cell datasets. Provides interface for comprehensively searching, browsing, visualizing and downloading functional state activity profiles of cancer single cells and corresponding PCGs/lncRNAs expression profiles.

Proper citation: CancerSEA (RRID:SCR_026155) Copy   

•   Source: SciCrunch Registry

http://gepia2.cancer-pku.cn/#index

Enhanced web server for large-scale expression profiling and interactive analysis. GEPIA2 is updated and enhanced version of GEPIA, offering more functionalities, higher resolution data analysis, and additional features like ability to analyze specific cancer subtypes, quantify gene signatures based on single-cell sequencing studies, and allow users to upload their own RNA-seq data for comparison with the TCGA and GTEx datasets; essentially providing more comprehensive and advanced platform for gene expression analysis compared to the original GEPIA version.

Proper citation: Gene Expression Profiling Interactive Analysis 2 (RRID:SCR_026154) Copy   

•   Source: SciCrunch Registry

https://github.com/zengxiaofei/HapHiC

Software fast, reference-independent, allele-aware scaffolding tool based on Hi-C data. Allele-aware scaffolding tool that uses Hi-C data to scaffold haplotype-phased genome assemblies into chromosome-scale pseudomolecules.

Proper citation: HapHiC (RRID:SCR_026284) Copy   

•   Source: SciCrunch Registry

https://pmc.ncbi.nlm.nih.gov/articles/PMC3783192/

Software tool for utilizing sequence intrinsic composition to classify protein-coding and long non-coding transcripts.

Proper citation: Coding-Non-Coding Index (RRID:SCR_026554) Copy   

•   Source: SciCrunch Registry

https://github.com/lvrgb777/STPoseNet

Source code for pose recognition model for laboratory mice based on yolov8. Real-time spatiotemporal network model for robust mouse pose estimation.

Proper citation: STPoseNet (RRID:SCR_026834) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/ggVennDiagram/readme/README.html

Software R package to generate Venn diagram.'ggplot2' implement of Venn Diagram.

Proper citation: ggVennDiagram (RRID:SCR_026950) Copy   

•   Source: SciCrunch Registry

https://github.com/BigDataBiology/SemiBin/

Software command tool for metagenomic binning with deep learning, handles both short and long reads. Used for metagenomic binning at contig level which uses deep contrastive learning.

Proper citation: SemiBin (RRID:SCR_026896) Copy   

•   Source: SciCrunch Registry

https://github.com/Baohua-Chen/GFFx

Software Rust-Based suite of utilities for ultra-fast genomic feature extraction. Used for ultra-fast and scalable genome annotation access. Can be used both as a command-line tool and as a Rust library.

Proper citation: GFFx (RRID:SCR_027445) Copy   

•   Source: SciCrunch Registry

https://github.com/The-Zhou-Lab/SeedGerm-VIG

Software pipeline to quantify seed vigour in wheat and other cereal crops using deep learning powered dynamic phenotypic analysis.

Proper citation: SeedGerm-VIG (RRID:SCR_027483) Copy   

•   Source: SciCrunch Registry

https://guolab.wchscu.cn/ImmuCellAI/#!/

Software tool for comprehensive T‐Cell subsets abundance prediction and its application in cancer immunotherapy.

Proper citation: ImmuCellAI (RRID:SCR_027645) 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://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

https://academic.oup.com/bioinformatics/article/34/7/1229/4657077

Software R/Shiny application for interactive creation of Circos plot. Used for creation of Circos plot interactively.

Proper citation: shinyCircoss (RRID:SCR_022367) 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