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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.

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On page 13 showing 241 ~ 260 out of 570 results
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  • RRID:SCR_002277

    This resource has 100+ mentions.

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   


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   


  • RRID:SCR_007037

    This resource has 5000+ mentions.

Issue

https://github.com/spm

Software package for analysis of brain imaging data sequences. Sequences can be a series of images from different cohorts, or time-series from same subject. Current release is designed for analysis of fMRI, PET, SPECT, EEG and MEG.

Proper citation: SPM (RRID:SCR_007037) Copy   


  • RRID:SCR_017621

    This resource has 1+ mentions.

https://github.com/schloi/MARVEL

Software set of tools that facilitate overlapping, patching, correction and assembly of noisy long reads.

Proper citation: Marvel (RRID:SCR_017621) Copy   


  • RRID:SCR_017118

    This resource has 1000+ mentions.

https://github.com/davidemms/OrthoFinder

Software Python application for comparative genomics analysis. Finds orthogroups and orthologs, infers rooted gene trees for all orthogroups and identifies all of gene duplcation events in those gene trees, infers rooted species tree for species being analysed and maps gene duplication events from gene trees to branches in species tree, improves orthogroup inference accuracy. Runs set of protein sequence files, one per species, in FASTA format.

Proper citation: OrthoFinder (RRID:SCR_017118) Copy   


  • RRID:SCR_016642

    This resource has 1+ mentions.

https://www.ncbi.nlm.nih.gov/sutils/pasc/viridty.cgi

Web tool for analysis of pairwise identity distribution within viral families. Used for virus sequence-based classification. Data in the system are updated every day to reflect changes in virus taxonomy and additions of new virus sequences to the public database.

Proper citation: PASC (RRID:SCR_016642) Copy   


  • RRID:SCR_018196

    This resource has 10+ mentions.

http://www.imgt.org/HighV-QUEST/home.action

Next generation B and T cell sequence alignment and characterization online surface by IMGT. Web portal for immunoglobulin (IG) or antibody and T cell receptor (TR) analysis from NGS high throughput and deep sequencing.

Proper citation: IMGT HighV-QUEST (RRID:SCR_018196) Copy   


  • RRID:SCR_014559

    This resource has 10+ mentions.

http://dynamine.ibsquare.be/submission/

An NMR based method for protein folding prediction. Users can enter a UniProt identifier, FASTA sequences, or upload a file containing FASTA sequences and results are returned., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DynaMine (RRID:SCR_014559) Copy   


  • RRID:SCR_015644

    This resource has 10000+ mentions.

http://www.cbs.dtu.dk/services/SignalP/

Web application for prediction of the presence and location of signal peptide cleavage sites in amino acid sequences from different organisms. The method incorporates a prediction of cleavage sites and a signal peptide/non-signal peptide prediction based on a combination of several artificial neural networks.

Proper citation: SignalP (RRID:SCR_015644) Copy   


  • RRID:SCR_000505

    This resource has 1+ mentions.

http://www.ifti.org/

A resource for information pertaining to methodologies, tools and technologies of gene expression. The website offers resources for sequence analysis, database services, and other technologies of gene expression and regulation.

Proper citation: IFTI-Mirage (RRID:SCR_000505) Copy   


  • RRID:SCR_016280

    This resource has 50+ mentions.

https://huttenhower.sph.harvard.edu/humann2

Software for profiling the presence/absence and abundance of microbial pathways in a community from metagenomic or metatranscriptomic sequencing data Used for millions of short DNA/RNA reads. This process, referred to as functional profiling, aims to describe the metabolic potential of a microbial community and its members.

Proper citation: HUMAnN2 (RRID:SCR_016280) Copy   


  • RRID:SCR_016338

    This resource has 10+ mentions.

https://github.com/Teichlab/tracer

Software application for recovery of T cell receptor (TCR) data from single cell data. Used to reconstruct full-length, paired T cell receptor (TCR) sequences from T lymphocyte single-cell RNA sequence data. Links T cell specificity with functional response by revealing clonal relationships between cells alongside their transcriptional profiles.

Proper citation: TraCeR (RRID:SCR_016338) Copy   


  • RRID:SCR_016507

    This resource has 100+ mentions.

https://cm.jefferson.edu/rna22/

Software tool as a pattern based algorithm for detecting microRNA binding sites and their corresponding microRNA and mRNA complexes. Allows interactive exploration and visualization of miRNA target predictions. Permits link-out to external expression repositories and databases.

Proper citation: RNA22 (RRID:SCR_016507) Copy   


  • RRID:SCR_016505

    This resource has 1+ mentions.

https://www.genome.jp/tools/dinies/

Web server for predicting unknown drug-target interaction networks from various types of biological data in the framework of supervised network inference.

Proper citation: DINIES (RRID:SCR_016505) Copy   


  • RRID:SCR_016504

    This resource has 100+ mentions.

http://www.compbio.dundee.ac.uk/jpred/

Software tool for protein secondary structure prediction from the amino acid sequence by the JNet algorithm. Makes also predictions on Solvent Accessibility and Coiled-coil regions.

Proper citation: Jpred (RRID:SCR_016504) Copy   


  • RRID:SCR_016473

    This resource has 1+ mentions.

http://bioinf.bio.uth.gr/nat-ncs2

Web server for the detection and evolutionary classification of prokaryotic and eukaryotic nucleobase-cation symporters of the NAT/NCS2 family. Used to scan, identify and evolutionary classify NAT/NCS2 nucleobase transporter proteins.

Proper citation: NAT/NCS2 Hound (RRID:SCR_016473) Copy   


  • RRID:SCR_016463

    This resource has 1+ mentions.

https://genome.jgi.doe.gov/programs/fungi/1000fungalgenomes.jsf

Web application to provide genomic information for fungi. Includes sequenced fungal genomes, those in progress, and selected nominations. Nomination of new species for genome sequencing in the families or only one reference genome possible after providing DNA/RNA samples for their sequencing. Used to explore the diversity of fungi important for energy and the environment.

Proper citation: 1000 Fungal Genome Project (RRID:SCR_016463) Copy   


  • RRID:SCR_016469

    This resource has 10+ mentions.

https://github.com/WGS-TB/MentaLiST

Software for a MLST (multi-locus sequence typing) caller, based on a k-mer counting algorithm and written in the Julia language. Designed and implemented to handle large typing schemes.

Proper citation: MentaLiST (RRID:SCR_016469) Copy   


  • RRID:SCR_016665

    This resource has 10+ mentions.

http://www.ccb.jhu.edu/software/centrifuge/

Software for rapid and sensitive classification of metagenomic sequences. Used for the classification of DNA sequences from microbial samples and analysis of large metagenomics data sets on conventional desktop computers.

Proper citation: Centrifuge Classifier (RRID:SCR_016665) Copy   


  • RRID:SCR_016599

    This resource has 100+ mentions.

https://pave.niaid.nih.gov

Collection of curated papillomavirus genomic sequences, accompanied by web-based sequence analysis tools. Database and web applications support the storage, annotation, analysis, and exchange of information.

Proper citation: PaVE (RRID:SCR_016599) Copy   



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