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http://array.mbb.yale.edu/analysis/

A fully integrated platform for processing microarray data.

Proper citation: ExpressYourself (RRID:SCR_008881) Copy   

•   Source: SciCrunch Registry

http://lemur.amu.edu.pl/share/php/mirnest/home.php

A database of animal, plant and virus microRNA data maintained at the University of Poznan. The database provides: * 9980 miRNA candiates from 420 animal and plant species predicted in Expressed Sequence Tags * predicted targets for plant candidates * RNA-seq reads mapped to candidates from 29 species * external data from 12 databases that includes sequences, polymorphism, expression and regulation. miRNEST 1.0, it contains miRNA from 563 animals, plants and viruses plant species.

Proper citation: miRNEST (RRID:SCR_008907) Copy   

•   Source: SciCrunch Registry

http://cbdb.nimh.nih.gov/microsniper/

A web-based application which predicts the impact of a SNP on putative microRNA targets.

Proper citation: MicroSNiPer (RRID:SCR_009880) Copy   

•   Source: SciCrunch Registry

http://www.phylogeny.fr/

A free, simple to use web service dedicated to reconstructing and analysing phylogenetic relationships between molecular sequences. Phylogeny.fr runs and connects various bioinformatics programs to reconstruct a robust phylogenetic tree from a set of sequences.

Proper citation: Phylogeny.fr (RRID:SCR_010266) Copy   

•   Source: SciCrunch Registry

http://hipathdb.kobic.re.kr/

hiPathDB is an integrated pathway database that combines the curated human pathway data of NCI-Nature PID, Reactome, BioCarta and KEGG. In total, it includes 1661 pathways consisting of 8976 distinct physical entities. (2010.03.09) hiPathDB provides two different types of integration. The pathway-level integration, conceptually a simple collection of individual pathways, was achieved by devising an elaborate model that takes distinct features of four databases into account and subsequently reformatting all pathways in accordance with our model. The entity-level integration creates a single unified pathway that encompasses all pathways by merging common components. Even though the detailed molecular-level information such as complex formation or post-translational modifications tends to be lost, such integration makes it possible to investigate signaling network over the entire pathways and allows identification of pathway cross-talks. Another strong merit of hiPathDB is the built-in pathway visualization module that supports explorative studies of complex networks in an interactive fashion. The layout algorithm is optimized for virtually automatic visualization of the pathways.

Proper citation: hiPathDB - human integrated Pathway DB with facile visualization (RRID:SCR_008900) Copy   

•   Source: SciCrunch Registry

http://www.medinfopoli.polimi.it/GFINDer/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 16, 2019. Multi-database system providing large-scale lists of user-classified sequence identifiers with genome-scale biological information and functional profiles biologically characterizing the different gene classes in the list. GFINDer automatically retrieves updated annotations of several functional categories from different sources, identifies the categories enriched in each class of a user-classified gene list, and calculates statistical significance values for each category. Moreover, GFINDer enables to functionally classify genes according to mined functional categories and to statistically analyze the obtained classifications, aiding in better interpreting microarray experiment results.

Proper citation: GFINDer: Genome Function INtegrated Discoverer (RRID:SCR_008868) Copy   

•   Source: SciCrunch Registry

http://centre.bioinformatics.zj.cn/mirtools/

A comprehensive web server developed to allow researchers to comprehensively characterize small RNA transcriptome.

Proper citation: mirTools (RRID:SCR_009701) Copy   

•   Source: SciCrunch Registry

http://hippocampome.org

A curated knowledge base of the circuitry of the hippocampus of normal adult, or adolescent, rodents at the mesoscopic level of neuronal types. Knowledge concerning dentate gyrus, CA3, CA2, CA1, subiculum, and entorhinal cortex is distilled from published evidence and is continuously updated as new information becomes available. Each reported neuronal property is documented with a pointer to, and excerpt from, relevant published evidence, such as citation quotes or illustrations. Please note: This is an alpha-testing site. The content is still being vetted for accuracy and has not yet undergone peer-review. As such, it may contain inaccuracies and should not (yet) be trusted as a scholarly resource. The content does not yet appear uniformly across all combinations of browsers and screen resolutions.

Proper citation: Hippocampome.org (RRID:SCR_009023) Copy   

•   Source: SciCrunch Registry

http://www.acedb.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 6th,2023. Software genome database management system.

Proper citation: AceDB (RRID:SCR_010671) Copy   

•   Source: SciCrunch Registry

http://www.ncbi.nlm.nih.gov/Structure/VAST/vast.shtml

VAST is a computer algorithm developed at NCBI and used to identify similar protein 3-dimensional structures by purely geometric criteria, and to identify distant homologs that cannot be recognized by sequence comparison. Related structures for every structure in MMDB are pre-computed using VAST and accessible via links on the MMDB Structure Summary pages. The VAST Search page also allows you to compare the coordinates of a newly resolved structure in PDB format against all structures in MMDB to find its neighbors. Protein structure neighbors in Entrez are determined by direct comparison of 3-dimensional protein structures with the VAST algorithm. Each of the more than 87,804 domains in MMDB is compared to every other one. From the MMDB Structure summary pages, retrieved via Entrez, structure neighbors are available for protein chains and individual structural domains. If you already know a PDB/MMDB-Id you can try this at once, using the input form in the right column. VAST Search is a service that allows searching for structural neighbors starting with a set of 3D-coordinates specified by the user. This service is meant to be used with newly determined protein structures that are not yet part of MMDB. Structure neighbors for proteins already in MMDB have been pre-computed and can simply be looked up from MMDB''s Structure summary pages!

Proper citation: Vector Alignment Search Tool (RRID:SCR_010655) Copy   

•   Source: SciCrunch Registry

http://tcoffee.crg.cat/apps/tcoffee/do:regular

A multiple sequence alignment server which can align Protein, DNA and RNA sequences.

Proper citation: T-Coffee (RRID:SCR_011818) Copy   

•   Source: SciCrunch Registry

http://diana.imis.athena-innovation.gr/DianaTools/index.php?r=lncBase/index

Database that hosts elaborated information for both predicted and experimentally verified, miRNA-lncRNA interactions. The database consists of two distinct modules. The Experimental Module contains detailed information for more than 5,000 interactions, between 2,958 lncRNAs and 120 miRNAs, ranging from miRNA and lncRNA related facts to information specific to their interaction, the experimental validation methodologies and their outcomes. The Prediction Module, which is based on the latest version of DIANA-microT target prediction algorithm (DIANA-microT-CDS), contains detailed information for more than 10 million interactions, between 56,097 lncRNAs and 3,078 miRNAs, ranging from miRNA and lncRNA related details to specific information regarding their interaction sites, graphical representation of their binding and the predicted score. This module exhibits a unique feature for searching the database. Users are able to add genomic locations to their queries thus browsing every miRNA-lncRNA interaction that has at least one MRE located inside the queried locus.

Proper citation: DIANA-LncBase (RRID:SCR_010840) Copy   

•   Source: SciCrunch Registry

http://probcons.stanford.edu/

Efficient protein multiple sequence alignment program, which has demonstrated a statistically significant improvement in accuracy compared to several leading alignment tools.

Proper citation: ProbCons (RRID:SCR_011813) Copy   

•   Source: SciCrunch Registry

http://www.rosaceae.org/

GDR is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, annotated EST databases of apple, peach, almond, cherry, rose, raspberry and strawberry, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, ORFs, Gene Ontology and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. We continue to add Rosaceae map data to CMap, a web-based tool that allows users to view comparisons of genetic and physical maps. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm, search their sequences for microsatellites using the SSR server or assemble their ESTs using the CAP3 Server.

Proper citation: Genome Database for Rosaceae (RRID:SCR_012756) Copy   

•   Source: SciCrunch Registry

http://nhjy.hzau.edu.cn/kech/swxxx/jakj/dianzi/Bioinf6/GeneFinding/GeneFinding2.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 10,2020. Data analysis service for Hidden Markov Model (HMM)-based gene structure prediction (multiple genes, both chains).

Proper citation: FGENESH (RRID:SCR_011928) Copy   

•   Source: SciCrunch Registry

http://race.unil.ch/

A collection of web tools designed to assist with the analysis of DNA microarray data and results. RACE performs probe level data preprocessing, quality checks, normalization, and visualization for Affymetrix GeneChips. In addition, it performs clustering and differential analysis of normalized expression levels or ratios for arbitrary platforms, and estimates the false discovery rates in lists of potentially regulated genes. A Gene Ontology (GO)-term analysis assists in the biological interpretation of gene lists. The user can customize each analysis request; upon submission the analysis is executed in a fully automated way., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: RACE (RRID:SCR_010950) Copy   

•   Source: SciCrunch Registry

http://www.imtech.res.in/raghava/hslpred/

A support vector machine (SVM)-based method for the prediction of 4 major subcellular localization (cytoplasm, mitochondrial, nuclear and plasma membrane) of human proteins using various features such as i) amino acid composition, ii) dipeptide composition and iii) evolutionary information of proteins.

Proper citation: HSLPred (RRID:SCR_011972) Copy   

•   Source: SciCrunch Registry

http://159.149.160.51/pscan_chip_dev/

Web server that, starting from a collection of genomic regions derived from a ChIP-Seq experiment, scans them using motif descriptors like JASPAR or TRANSFAC position-specific frequency matrices, or descriptors uploaded by users, and it evaluates both motif enrichment and positional bias within the regions according to different measures and criteria.

Proper citation: Pscan-ChIP (RRID:SCR_010885) Copy   

•   Source: SciCrunch Registry

http://mbgd.genome.ad.jp/

MBGD is a database for comparative analysis of completely sequenced microbial genomes, the number of which is now growing rapidly. The aim of MBGD is to facilitate comparative genomics from various points of view such as ortholog identification, paralog clustering, motif analysis and gene order comparison. The heart of MBGD function is to create orthologous or homologous gene cluster table. For this purpose, similarities between all genes are precomputed and stored into the database, in addition to the annotations of genes such as function categories that were assigned by the original authors and motifs that were found in the translated sequence. Using these homology data, MBGD dynamically creates orthologous gene cluster table. Users can change a set of organisms or cutoff parameters to create their own orthologous grouping. Based on this cluster table, users can further analyze multiple genomes from various points of view with the functions such as global map comparison, local map comparison, multiple sequence alignment and phylogenetic tree construction.

Proper citation: MBGD - Microbial Genome Database (RRID:SCR_012824) Copy   

•   Source: SciCrunch Registry

http://cupsat.tu-bs.de/

A tool to predict changes in protein stability upon point mutations.

Proper citation: CUPSAT (RRID:SCR_010773) Copy   

•   Source: SciCrunch Registry