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https://github.com/Sung-Huan/ANNOgesic

Software tool for bacterial/archaeal RNA-Seq based genome annotations. Used for integrating, detecting, predicting, and grouping RNA-Seq data.

Proper citation: ANNOgesic (RRID:SCR_016326) Copy   

•   Source: SciCrunch Registry

https://chordate.bpni.bio.keio.ac.jp/chordate/faba/1.4/top.html

Image resource including ascidian's three-dimensional (3D) and cross-sectional images through the developmental time course. These images were reconstructed from more than 3,000 high-resolution real images collected by confocal laser scanning microscopy (CLSM) at newly defined 26 distinct developmental stages (stages 1-26) from fertilized egg to hatching larva, which were grouped into six periods named the zygote, cleavage, gastrula, neurula, tailbud, and larva periods. The data set will be helpful in standardizing developmental stages for morphology comparison as well as for providing guidelines for several functional studies of a body plan in chordate.

Proper citation: Four-dimensional Ascidian Body Atlas (RRID:SCR_001691) Copy   

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http://mech.ctb.pku.edu.cn/protisa/

Database of confirmed translation initiation sites (TISs) for prokaryotic genomes. The confirmed data has supporting evidence from different sources, including experiments records in the public protein database Swiss-Prot, literature, conserved domain search and sequence alignment among orthologous genes. Combing with predictions from the-state-of-the-art TIS predictor MED-Start/MED-StartPlus (in release 1.0 & 1.2) and TriTISA (since release 1.4) and annotations on potential regulatory signals, the database can serve as a refined annotation resource for the public database RefSeq.

Proper citation: ProTISA (RRID:SCR_002138) Copy   

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http://megasun.bch.umontreal.ca/ogmpproj.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. It investigates mitochondrial genome diversity and evolution by systematically determining the complete mitochondrial DNA (mtDNA) sequences of a phylogenetically broad selection of protists. The mtDNAs of lower fungi and choanoflagellates are being analyzed by the Fungal Mitochondrial Genome Project (FMGP), a sister project to the OGMP.

Proper citation: Organelle Genomics (RRID:SCR_002137) Copy   

•   Source: SciCrunch Registry

http://pallab.serc.iisc.ernet.in/gester/

Database of intrinsic terminators of transcription that is comprized of >2,200,000 bacterial terminators identified from a total of 2036 chromosomes and 1508 plasmids. Information about structural parameters of individual terminators such as sequence, length of stem and loop, mismatches and gaps, U-trail, genomic coordinates and gene name and accession number is available in both tabular form and as a composite figure. Summary statistics for terminator profiles of whole genome can be also obtained. Raw data files for individual genomes can be downloaded (.zip files) for detailed investigations. Data is organized into different tiers such that users can fine-tune their search by entering name of the species, or taxon ID or genomes with a certain number of terminators. To visualize the occurrence of the terminators, an interactive map, with the resolution to single gene level, has been developed.

Proper citation: WebGeSTer DB (RRID:SCR_002165) Copy   

•   Source: SciCrunch Registry

https://www.bgee.org/

Database to retrieve and compare gene expression patterns between animal species. Bgee first maps heterogeneous expression data (currently bulk RNA-Seq, scRNA-Seq, Affymetrix, in situ hybridization, and EST data) to anatomy and development of different species. Bgee is based exclusively on curated healthy wild-type expression data (e.g., no gene knock-out, no treatment, no disease), to provide a comparable reference of gene expression.

Proper citation: Bgee: dataBase for Gene Expression Evolution (RRID:SCR_002028) Copy   

•   Source: SciCrunch Registry

https://enigma.lbl.gov/regprecise/

Collection of manually curated inferences of regulons in prokaryotic genomes. Database for capturing, visualization and analysis of transcription factor regulons that were reconstructed by comparative genomic approach in wide variety of prokaryotic genomes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RegPrecise (RRID:SCR_002149) Copy   

•   Source: SciCrunch Registry

http://giladlab.uchicago.edu/orthoExon/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Database of orthologous exon regions in the genomes of human, chimpanzee, and rhesus macaque. It can be used in analysis of multi-species RNA-seq expression data, allowing for comparisons of exon-level expression across primates, as well as comparative examination of alternative splicing and transcript isoforms.

Proper citation: Primate Orthologous Exon Database (RRID:SCR_002065) Copy   

•   Source: SciCrunch Registry

http://www.nih.gov/science/models/rat/

The Rat Genome Program was launched after the National Institutes of Health (NIH) realized the potential of rat models in understanding basic biology and human health and disease. The purpose of this NIH Rat Genomics and Genetics web site is to serve as a central point for information on NIH sponsored and related rat genetic and genomic activities and resources. It will provide information on: the follow up to recommendations made to the NIH; funding opportunities for rat genomic and genetic tools and resources; major rat genomic resources available and/or produced in response to the NIH Rat Program; courses and meetings related to rat genomics and genetics; and selected reports and publications. These programs have produced a wide variety of resources and a way to link and capitalize upon the data and resources of other model organisms and the human. In conjunction with and in addition to these programs, the NIH, through the RGWG, has convened advisory groups and workshops to discuss the opportunities that rat models offer and provide recommendations on the investments that are needed to capitalize on these opportunities.

Proper citation: NIH Rat Genomics and Genetics (RRID:SCR_002267) Copy   

•   Source: SciCrunch Registry

http://cancer.sanger.ac.uk/cancergenome/projects/cosmic/

Database to store and display somatic mutation information and related details and contains information relating to human cancers. The mutation data and associated information is extracted from the primary literature. In order to provide a consistent view of the data a histology and tissue ontology has been created and all mutations are mapped to a single version of each gene. The data can be queried by tissue, histology or gene and displayed as a graph, as a table or exported in various formats.
Some key features of COSMIC are:
* Contains information on publications, samples and mutations. Includes samples which have been found to be negative for mutations during screening therefore enabling frequency data to be calculated for mutations in different genes in different cancer types.
* Samples entered include benign neoplasms and other benign proliferations, in situ and invasive tumours, recurrences, metastases and cancer cell lines.

Proper citation: COSMIC - Catalogue Of Somatic Mutations In Cancer (RRID:SCR_002260) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/swissprot/hpi/hpi.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 03, 2011. IT HAS BEEN REPLACED BY A NEW UniProtKB/Swiss-Prot ANNOTATION PROGRAM CALLED UniProt Chordata protein annotation program. The Human Proteome Initiative (HPI) aims to annotate all known human protein sequences, as well as their orthologous sequences in other mammals, according to the quality standards of UniProtKB/Swiss-Prot. In addition to accurate sequences, we strive to provide, for each protein, a wealth of information that includes the description of its function, domain structure, subcellular location, similarities to other proteins, etc. Although as complete as currently possible, the human protein set they provide is still imperfect, it will have to be reviewed and updated with future research results. They will also create entries for newly discovered human proteins, increase the number of splice variants, explore the full range of post-translational modifications (PTMs) and continue to build a comprehensive view of protein variation in the human population. The availability of the human genome sequence has enabled the exploration and exploitation of the human genome and proteome to begin. Research has now focused on the annotation of the genome and in particular of the proteome. With expert annotation extracted from the literature by biologists as the foundation, it has been possible to expand into the areas of data mining and automatic annotation. With further development and integration of pattern recognition methods and the application of alignments clustering, proteome analysis can now be provided in a meaningful way. These various approaches have been integrated to attach, extract and combine as much relevant information as possible to the proteome. This resource should be valuable to users from both research and industry. We maintain a file containing all human UniProtKB/Swiss-Prot entries. This file is updated at every biweekly release of UniProt and can be downloaded by FTP download, HTTP download or by using a mirroring program which automatically retrieves the file at regular intervals.

Proper citation: Human Proteomics Initiative (RRID:SCR_002373) Copy   

•   Source: SciCrunch Registry

http://bibiserv.techfak.uni-bielefeld.de/agt-sdp/

Database providing automatic test cases for protein-protein docking. A consensus-type approach is proposed processing the whole PDB and classifying protein structures into complexes and unbound proteins by combining information from three different approaches. Out of this classification test cases are generated automatically. All calculations were run on the database. The information stored is available via a web interface. The user can choose several criteria for generating his own subset out of the test cases, e.g. for testing docking algorithms. In unbound protein--protein docking, the complex of two proteins is predicted using the unbound conformations of the proteins (Halperin et al.,2002). For testing of docking algorithms, two unbound proteins which form a known complex have to be identified, so that the result of the docking algorithm can be compared to the known complex. For the identification of test cases, the structures taken from the PDB have to be classified as unbound proteins or complexes and unbound proteins with a 100% sequence identity to one complex part have to be searched. By now, most groups use handpicked test sets. The largest collection of test cases used so far is described by Chen et al. (Chen et al.,2003) and contains 31 test cases for unbound docking. Because of the exponential growth of available protein structures in the PDB, automatic generation of test cases will become more and more important in the future.

Proper citation: Automatic Generated Test-Sets Database for Protein-Protein Docking (RRID:SCR_002281) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/ieb/research/acembly/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented August 29, 2016. AceView offers an integrated view of the human, nematode and Arabidopsis genes reconstructed by co-alignment of all publicly available mRNAs and ESTs on the genome sequence. Our goals are to offer a reliable up-to-date resource on the genes and their functions and to stimulate further validating experiments at the bench. AceView provides a curated, comprehensive and non-redundant sequence representation of all public mRNA sequences (mRNAs from GenBank or RefSeq, and single pass cDNA sequences from dbEST and Trace). These experimental cDNA sequences are first co-aligned on the genome then clustered into a minimal number of alternative transcript variants and grouped into genes. Using exhaustively and with high quality standards the available cDNA sequences evidences the beauty and complexity of mammals' transcriptome, and the relative simplicity of the nematode and plant transcriptomes. Genes are classified according to their inferred coding potential; many presumably non-coding genes are discovered. Genes are named by Entrez Gene names when available, else by AceView gene names, stable from release to release. Alternative features (promoters, introns and exons, polyadenylation signals) and coding potential, including motifs, domains, and homologies are annotated in depth; tissues where expression has been observed are listed in order of representation; diseases, phenotypes, pathways, functions, localization or interactions are annotated by mining selected sources, in particular PubMed, GAD and Entrez Gene, and also by performing manual annotation, especially in the worm. In this way, both the anatomy and physiology of the experimentally cDNA supported human, mouse and nematode genes are thoroughly annotated. Our goals are to offer an up-to-date resource on the genes, in the hope to stimulate further experiments at the bench, or to help medical research. AceView can be queried by meaningful words or groups of words as well as by most standard identifiers, such as gene names, Entrez Gene ID, UniGene ID, GenBank accessions.

Proper citation: AceView (RRID:SCR_002277) Copy   

•   Source: SciCrunch Registry

http://fullmal.hgc.jp/index_ajax.html

FULL-malaria is a database for a full-length-enriched cDNA library from the human malaria parasite Plasmodium falciparum. Because of its medical importance, this organism is the first target for genome sequencing of a eukaryotic pathogen; the sequences of two of its 14 chromosomes have already been determined. However, for the full exploitation of this rapidly accumulating information, correct identification of the genes and study of their expression are essential. Using the oligo-capping method, this database has produced a full-length-enriched cDNA library from erythrocytic stage parasites and performed one-pass reading. The database consists of nucleotide sequences of 2490 random clones that include 390 (16%) known malaria genes according to BLASTN analysis of the nr-nt database in GenBank; these represent 98 genes, and the clones for 48 of these genes contain the complete protein-coding sequence (49%). On the other hand, comparisons with the complete chromosome 2 sequence revealed that 35 of 210 predicted genes are expressed, and in addition led to detection of three new gene candidates that were not previously known. In total, 19 of these 38 clones (50%) were full-length. From these observations, it is expected that the database contains approximately 1000 genes, including 500 full-length clones. It should be an invaluable resource for the development of vaccines and novel drugs. Full-malaria has been updated in at least three points. (i) 8934 sequences generated from the addition of new libraries added so that the database collection of 11,424 full-length cDNAs covers 1375 (25%) of the estimated number of the entire 5409 parasite genes. (ii) All of its full-length cDNAs and GenBank EST sequences were mapped to genomic sequences together with publicly available annotated genes and other predictions. This precisely determined the gene structures and positions of the transcriptional start sites, which are indispensable for the identification of the promoter regions. (iii) A total of 4257 cDNA sequences were newly generated from murine malaria parasites, Plasmodium yoelii yoelii. The genome/cDNA sequences were compared at both nucleotide and amino acid levels, with those of P.falciparum, and the sequence alignment for each gene is presented graphically. This part of the database serves as a versatile platform to elucidate the function(s) of malaria genes by a comparative genomic approach. It should also be noted that all of the cDNAs represented in this database are supported by physical cDNA clones, which are publicly and freely available, and should serve as indispensable resources to explore functional analyses of malaria genomes. Sponsors: This database has been constructed and maintained by a Grant-in-Aid for Publication of Scientific Research Results from the Japan Society for the Promotion of Science (JSPS). This work was also supported by a Special Coordination Funds for Promoting Science and Technology from the Science and Technology Agency of Japan (STA) and a Grant-in-Aid for Scientific Research on Priority Areas from the Ministry of Education, Science, Sports and Culture of Japan.

Proper citation: Full-Malaria: Malaria Full-Length cDNA Database (RRID:SCR_002348) Copy   

•   Source: SciCrunch Registry

http://hgc.rockefeller.edu/

An interactive web server that enables researchers to prioritize any list of genes by their biological proximity to defined core genes (i.e. genes that are known to be associated with the phenotype), and to predict novel gene pathways.

Proper citation: Human Gene Connectome Server (RRID:SCR_002627) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/RefSeq/

Collection of curated, non-redundant genomic DNA, transcript RNA, and protein sequences produced by NCBI. Provides a reference for genome annotation, gene identification and characterization, mutation and polymorphism analysis, expression studies, and comparative analyses. Accessed through the Nucleotide and Protein databases.

Proper citation: RefSeq (RRID:SCR_003496) Copy   

•   Source: SciCrunch Registry

http://genomequebec.mcgill.ca/PReMod

Database that describes more than 100,000 computational predicted transcriptional regulatory modules within the human genome. These modules represent the regulatory potential for 229 transcription factors families and are the first genome-wide / transcription factor-wide collection of predicted regulatory modules for the human genome. The algorithm used involves two steps: (i) Identification and scoring of putative transcription factor binding sites using 481 TRANSFAC 7.2 position weight matrices (PWMs) for vertebrate transcription factors. To this end, each non-coding position of the human genome was evaluated for its similarity to each PWM using a log-likelihood ratio score with a local GC-parameterized third-order Markov background model. Corresponding orthologous positions in mouse and rat genomes were evaluated similarly and a weighted average of the human, mouse, and rat log-likelihood scores at aligned positions (based on a Multiz (Blanchette et al. 2004) genome-wide alignment of these three species) was used to define the matrix score for each genomic position and each PWM. (ii) Detection of clustered putative binding sites. To assign a module score to a given region, the five transcription factors with the highest total scoring hits are identified, and a p-value is assigned to the total score observed of the top 1, 2, 3, 4, or 5 factors. The p-value computation takes into consideration the number of factors involved (1 to 5), their total binding site scores, and the length and GC content of the region under evaluation. Users can retrieve all information for a given region, a given PWM, a given gene and so on. Several options are given for textual output or visualization of the data.

Proper citation: PReMod (RRID:SCR_003403) Copy   

•   Source: SciCrunch Registry

http://www-bio3d-igbmc.u-strasbg.fr/ICDS/

Database of interrupted coding sequences detected by a similarity-based approach in complete prokaryotic genomes. The definition of each interrupted gene is provided as well as the ICDS genomic localization with the surrounding sequence. To facilitate the experimental characterization of ICDS, optimized primers are proposed for re-sequencing purposes. The database is accessible by BLAST search or by genome. 118 Genomes are available in the database.

Proper citation: Interrupted CoDing Sequence Database (RRID:SCR_002949) Copy   

•   Source: SciCrunch Registry

http://mirnamap.mbc.nctu.edu.tw

A database of experimentally verified microRNAs and miRNA target genes in human, mouse, rat, and other metazoan genomes. In addition to known miRNA targets, three computational tools previously developed, such as miRanda, RNAhybrid and TargetScan, were applied for identifying miRNA targets in 3'-UTR of genes. In order to reduce the false positive prediction of miRNA targets, several criteria are supported for filtering the putative miRNA targets. Furthermore, miRNA expression profiles can provide valuable clues for investigating the properties of miRNAs, such tissue specificity and differential expression in cancer/normal cell. Therefore, we performed the Q-PCR experiments for monitoring the expression profiles of 224 human miRNAs in eighteen major normal tissues in human. The cross-reference between the miRNA expression profiles and the expression profiles of its target genes can provide effective viewpoint to understand the regulatory functions of the miRNA.

Proper citation: miRNAMap (RRID:SCR_003156) Copy   

•   Source: SciCrunch Registry

http://bioinfo.mbi.ucla.edu/ASAP/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on 8/12/13. Database to access and mine alternative splicing information coming from genomics and proteomics based on genome-wide analyses of alternative splicing in human (30 793 alternative splice relationships found) from detailed alignment of expressed sequences onto the genomic sequence. ASAP provides precise gene exon-intron structure, alternative splicing, tissue specificity of alternative splice forms, and protein isoform sequences resulting from alternative splicing. They developed an automated method for discovering human tissue-specific regulation of alternative splicing through a genome-wide analysis of expressed sequence tags (ESTs), which involves classifying human EST libraries according to tissue categories and Bayesian statistical analysis. They use the UniGene clusters of human Expressed Sequence Tags (ESTs) to identify splices. The UniGene EST's are clustered so that a single cluster roughly corresponds to a gene (or at least a part of a gene). A single EST represents a portion of a processed (already spliced) mRNA. A given cluster contains many ESTs, each representing an outcome of a series of splicing events. The ESTs in UniGene contain the different mRNA isoforms transcribed from an alternatively spliced gene. They are not predicting alternative splicing, but locating it based on EST analysis. The discovered splices are further analyzed to determine alternative splicing events. They have identified 6201 alternative splice relationships in human genes, through a genome-wide analysis of expressed sequence tags (ESTs). Starting with 2.1 million human mRNA and EST sequences, they mapped expressed sequences onto the draft human genome sequence and only accepted splices that obeyed the standard splice site consensus. After constructing a tissue list of 46 human tissues with 2 million human ESTs, they generated a database of novel human alternative splices that is four times larger than our previous report, and used Bayesian statistics to compare the relative abundance of every pair of alternative splices in these tissues. Using several statistical criteria for tissue specificity, they have identified 667 tissue-specific alternative splicing relationships and analyzed their distribution in human tissues. They have validated our results by comparison with independent studies. This genome-wide analysis of tissue specificity of alternative splicing will provide a useful resource to study the tissue-specific functions of transcripts and the association of tissue-specific variants with human diseases.

Proper citation: ASAP: the Alternative Splicing Annotation Project (RRID:SCR_003415) Copy   

•   Source: SciCrunch Registry