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http://bioinformatics.biol.uoa.gr/PRED-TMBB/
A web tool, based on a Hidden Markov Model, capable of predicting the transmembrane beta-strands of the gram-negative bacteria outer membrane proteins, and of discriminating such proteins from water-soluble ones when screening large datasets. The model is trained in a discriminative manner, aiming at maximizing the probability of the correct prediction rather than the likelihood of the sequences. The training is performed on a non-redundant database consisting of 16 outer membrane proteins (OMP''s) with their structures known at atomic resolution. We show that we can achieve predictions at least as good comparing with other existing methods, using as input only the amino-acid sequence, without the need of evolutionary information included in multiple alignments. The method is also powerful when used for discrimination purposes, as it can discriminate with a high accuracy the outer membrane proteins from water soluble in large datasets, making it a quite reliable solution for screening entire genomes. This web-server can help you run a discriminating process on any amino-acid sequence and thereafter localize the transmembrane strands and find the topology of the loops.
Proper citation: PRED-TMBB (RRID:SCR_006190) Copy
http://bioapps.rit.albany.edu/MITOPRED/
THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. It predicts nuclear-encoded mitochondrial proteins from all eukaryotic species including plants. Prediction is based on the occurrence patterns of Pfam domains (version 16.0) in different cellular locations, amino acid composition and pI value differences between mitochondrial and non-mitochondrial locations. Additionally, you may download MITOPRED predictions for complete proteomes. Re-calculated predictions are instantly accessible for proteomes of Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila, Homo sapiens, Mus musculus and Arabidopsis species as well as all the eukaryotic sequences in the Swiss-Prot and TrEMBL databases. Queries, at different confidence levels, can be made through four distinct options: (i) entering Swiss-Prot/TrEMBL accession numbers; (ii) uploading a local file with such accession numbers; (iii) entering protein sequences; (iv) uploading a local file containing protein sequences in FASTA format. The Mitopred algorithm works based on the differences in the Pfam domain occurrence patters and amino acid composition differences in different cellular compartments. Location specific Pfam domains have been determined from the entire eukaryotic set of Swissprot database. Similarly, differences in the amino acid composition between mitochondrial and non-mitochondrial sequences were pre-calculated. This information is used to calculate location-specific amino acid weights that are used to calculate amino acid score. Similarly, pI average values of the N-terminal 25 residues in different cellular location were also determined. This knowledge-base is accessed by the program during execution.
Proper citation: mitopred (RRID:SCR_006135) Copy
http://genetrail.bioinf.uni-sb.de/
A web-based application that analyzes gene sets for statistically significant accumulations of genes that belong to some functional category. Considered category types are: KEGG Pathways, TRANSPATH Pathways, TRANSFAC Transcription Factor, GeneOntology Categories, Genomic Localization, Protein-Protein Interactions, Coiled-coil domains, Granzyme-B clevage sites, and ELR/RGD motifs. The web server provides two statistical approaches, "Over-Representation Analysis" (ORA) comparing a reference set of genes to a test set, and "Gene Set Enrichment Analysis" (GSEA) scoring sorted lists of genes., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GeneTrail (RRID:SCR_006250) Copy
http://omicslab.genetics.ac.cn/GOEAST/
Gene Ontology Enrichment Analysis Software Toolkit (GOEAST) is a web based software toolkit providing easy to use, visualizable, comprehensive and unbiased Gene Ontology (GO) analysis for high-throughput experimental results, especially for results from microarray hybridization experiments. The main function of GOEAST is to identify significantly enriched GO terms among give lists of genes using accurate statistical methods. Compared with available GO analysis tools, GOEAST has the following unique features: * GOEAST supports analysis for data from various resources, such as expression data obtained using Affymetrix, illumina, Agilent or customized microarray platforms. GOEAST also supports non-microarray based experimental data. The web-based feature makes GOEAST very user friendly; users only have to provide a list of genes in correct formats. * GOEAST provides visualizable analysis results, by generating graphs exhibiting enriched GO terms as well as their relationships in the whole GO hierarchy. * Note that GOEAST generates separate graph for each of the three GO categories, namely biological process, molecular function and cellular component. * GOEAST allows comparison of results from multiple experiments (see Multi-GOEAST tool). The displayed color of each GO term node in graphs generated by Multi-GOEAST is the combination of different colors used in individual GOEAST analysis. Platform: Online tool
Proper citation: GOEAST - Gene Ontology Enrichment Analysis Software Toolkit (RRID:SCR_006580) Copy
http://tools.neb.com/NEBcutter2/
This tool will take a DNA sequence and find the large, non-overlapping open reading frames using the E.coli genetic code and the sites for all Type II and commercially available Type III restriction enzymes that cut the sequence just once. By default, only enzymes available from NEB are used, but other sets may be chosen. Just enter your sequence and submit. Further options will appear with the output. The maximum size of the input file is 1 MByte, and the maximum sequence length is 300 KBases. NEBcutter produces a variety of outputs including restriction enzyme maps, theoretical digests and links into the restriction enzyme database, REBASE (http://rebase.neb.com/rebase/rebase.html). Importantly, its table of recognition sites is updated daily from REBASE and it marks all sites that are potentially affected by DNA methylation (Dam, Dcm, etc.). Many options exist to choose the enzymes used for digestion, including all known specificities, subsets of those that are commercially available or sets of enzymes that produce compatible termini.
Proper citation: NEBcutter (RRID:SCR_010664) Copy
http://gump.qimr.edu.au/general/daleN/SNPSpD/
SNPSpD is a method of correcting for non-independance of single nucleotide polymorphisms (SNPs) in linkage disequilibrium (LD) with each other, on the basis of the spectral decomposition (SpD) of matrices of LD between SNP''s. Additionally, output from SNPSpD includes eigenvalues, principal-component coefficients, and factor loadings after varimax rotation, enabling the selection of a subset of SNPs that optimize the information in a genomic region.
Proper citation: Single Nucleotide Polymorphism Spectral Decomposition (SNPSpD) (RRID:SCR_008621) Copy
http://wwwmgs.bionet.nsc.ru/mgs/programs/panalyst/
WebProAnalyst provides web-accessible analysis for scanning the quantitative structure-activity relationships in protein families. It searches for a sequence region, whose substitutions are correlated with variations in the activities of a homologous protein set, the so-called activity modulating sites. WebProAnalyst allows users to search for the key physicochemical characteristics of the sites that affect the changes in protein activities. It enables the building of multiple linear regression and neural networks models that relate these characteristics to protein activities. WebProAnalyst implements multiple linear regression analysis, back propagation neural networks and the Structure-Activity Correlation/Determination Coefficient (SACC/SADC). A back propagation neural network is implemented as a two-layered network, one layer as input, the other as output (Rumelhart et al, 1986). WebProAnalyst uses alignment of amino acid sequences and data on protein activity (pK, Km, ED50, among others). The input data are the numerical values for the physicochemical characteristics of a site in the multiple alignment given by a slide window. The output data are the predicted activity values. The current version of WebProAnalyst handles a single activity for a single protein. The SACC/SADC may be defined as an estimate of the strongest multiple correlation between the physicochemical characteristics of a site in a multiple alignment and protein activities. The SACC/SADC coefficient makes possible the calculation of the possible highest correlation achievable for the quantitative relationship between the physicochemical properties of sites and protein activities. The SACC/SADC is a convenient means for an arrangement of positions by their functional significance. WebProAnalyst outputs a list of multiple alignment positions, the respective correlation values, also regression analysis parameters for the relationships between the amino acid physicochemical characteristics at these positions and the protein activity values.
Proper citation: Webproanalyst (RRID:SCR_008348) Copy
https://dogma.ccbb.utexas.edu/
Web-based annotation tool for plant chloroplasts and animal mitochondrial genomes. DOGMA allows the use of BLAST searches against a custom database, and conservation of basepairing in the secondary structure of animal mitochondrial tRNAs to identify and annotate genes.
Proper citation: DOGMA (RRID:SCR_015060) Copy
http://floresta.eead.csic.es/primers4clades
Web application for the design of PCR primers for cross-species amplification of novel sequences from metagenomic DNA or from uncharacterized organisms belonging to user-specified phylogenetic lineages. It implements an extended CODEHOP strategy and evaluates thermodynamic properties of the oligonucleotide pairs.
Proper citation: primers4clades (RRID:SCR_015714) Copy
https://github.com/esctrionsit/snphub
Web Shiny-based server framework for retrieving, analyzing and visualizing large genomic variations data.
Proper citation: SnpHub (RRID:SCR_018177) Copy
https://github.com/WangHYLab/fcirc
Software Python pipeline for linear and circular RNAs of known fusions exploration. Pipeline for exploring linear transcripts and circRNAs of known fusions based on RNA-Seq data. Known fusion genes are from multiple databases like COSMIC, ChimerDB, TicDB, FARE-CAFE and FusionCancer or user-added gene-pairs.
Proper citation: Fcirc (RRID:SCR_018090) Copy
https://github.com/bcgsc/NanoSim
Software tool as Nanopore sequence read simulator based on statistical characterization. Oxford Nanopore Technology sequence simulator written in Python and R. Benefits development of scalable next generation sequencing technologies for long nanopore reads, including genome assembly, mutation detection, and metagenomic analysis software.
Proper citation: NanoSim (RRID:SCR_018243) Copy
https://www.biosimulations.org/
Web tool for sharing and re-using biomodels, simulations, and visualizations of simulations results. Supports variety of modeling frameworks including kinetic, constraint based, and logical modeling, model formats including BNGL, CellML, SBML, and simulation tools including COPASI, libRoadRunner/tellurium, NFSim, VCell.
Proper citation: BioSimulations (RRID:SCR_018733) Copy
http://sysbio.rnet.missouri.edu/multicom_toolbox/NNCon%201.0.html
Protein contact map prediction is useful for protein folding rate prediction, model selection and 3D structure prediction. Here we describe NNcon, a fast and reliable contact map prediction server and software. NNcon was ranked among the most accurate residue contact predictors in the Eighth Critical Assessment of Techniques for Protein Structure Prediction (CASP8), 2008.
Proper citation: NNcon (RRID:SCR_014292) Copy
http://www.benoslab.pitt.edu/comir/
Data analysis service that predicts whether a given mRNA is targeted by a set of miRNAs. ComiR uses miRNA expression to improve and combine multiple miRNA targets for each of the four prediction algorithms: miRanda, PITA, TargetScan and mirSVR. The composite scores of the four algorithms are then combined using a support vector machine trained on Drosophila Ago1 IP data.
Proper citation: ComiR (RRID:SCR_013023) Copy
http://tools.genxpro.net/omiras/
A web server for the annotation, comparison and visualization of interaction networks of non-coding RNAs derived from small RNA-Sequencing experiments of two different conditions.
Proper citation: omiRas (RRID:SCR_010833) Copy
http://www.mutationtaster.org/
Evaluates disease-causing potential of sequence alterations.
Proper citation: MutationTaster (RRID:SCR_010777) Copy
A sequence verification pipeline where users can submit trace files to verify if a clone''s physical sequence matches its reference sequence.
Proper citation: GenoREAD (RRID:SCR_012007) Copy
A web server designed to provide a total solution to analyze small RNAs sequencing data generated by SOLEXA., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: DSAP (RRID:SCR_013352) Copy
PubCrawler is a free alerting service that scans daily updates to the NCBI Medline (PubMed) and GenBank databases. PubCrawler helps keeping scientists informed of the current contents of Medline and GenBank, by listing new database entries that match their research interests. The free PubCrawler web service has been operating for five years and so far has brought literature and sequence updates to over 22 000 users. It provides information on a personalized web page whenever new articles appear in PubMed or when new sequences are found in GenBank that are specific to customized queries. The server also acts as an automatic alerting system by sending out short notifications or emails with the latest updates as soon as they become available. PubCrawler searches the NCBI PubMed (Medline) and Entrez (GenBank) databases daily using search parameters (keywords, author names, etc.) specified by the user. There is no limit on the number of searches that can be carried out. Previous search hits are stored and only the newest PubMed or GenBank records are shown each day. The results are presented as an HTML Web page, similar to the results of an NCBI PubMed or Entrez query. This Web page can be located on our computer (the PubCrawler WWW-Service), on your computer (the stand-alone program), or you can receive it via e-mail (set this up using the PubCrawler WWW-Service). The Web page sorts the results into groups of PubMed/GenBank entries that are zero-days-old, 1-day-old, 2-days-old, etc., up to a user-specified age limit. Sponsors: Development of PubCrawler was supported by EMBnet
Proper citation: PubCrawler (RRID:SCR_008235) Copy
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