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APPRIS
The main goal of developing the APPRIS WebServer and WebServices is to allow users to annotate splice isoforms and select a principal isoform for vertebrate genome species beyond those that are annotated in the APPRIS Database, to annotate genes and variants that are missing from the APPRIS Database, and to annotate their experimental results with existing annotations. The APPRIS WebServer has been designed to be used for the comparison of splice isoform annotations for individual genes, while the APPRIS WebServices have been created to allow access to the APPRIS Database and to run an automatic version of the APPRIS server, using REST architecture to be portable, modular and flexible in the automation of programmatic scripts.
rPGA / RNA-seq Personal Genome-alignment Analyzer
Allows users to discover hidden splice junctions by mapping personal RNA-seq data to the matching personal genome sequence. rPGA personalizes the reference genome according to an individual’s single nucleotide polymorphisms (SNPs) and then maps the individual’s transcriptome to the corresponding personal genome, and discovers novel splice variants specific to the individual. This software was applied to analyze RNA-seq data from individuals with whole-genome genotype data in the 1000 Genomes project.
Exogean / EXpert On GEne Annotation
Predicts transcripts human mRNA and mouse protein sequence alignments. Exogean enables prediction of several alternative transcripts per gene. It can be useful for annotation of eukaryote protein coding genes based on alignments with proteins from a different species and/or mRNAs from the same species. This tool produces information on each predicted gene and transcript that summarizes their structure, the evidence used, the problems and conflicts encountered and the solutions applied.
FSOM
A computational technique for the study of stable methylation patterns which is a crucial piece of the puzzle in the attempt to understand the influence of DNA methylation on the regulation of alternative splicing. FSOM is able to determine stable methylation patterns and allows to correlate these patterns with inclusion propensity of exons. Pattern detection is based on dynamic time warping (DTW) of methylation profiles, a sophisticated similarity measure for signals that can be non-trivially transformed.
RASE / Recognition of alternatively Spliced Exons in C. elegans
Provides a support vector machine (SVM) kernel which aims to classify sequences by motifs. RASE is composed of two algorithms which allows users to identify hypothetic spliced exons thanks to confirmed exons and introns. Moreover, it can also locate a specific exon within an intron and be applied to scan over all Expressed Sequence Tag (EST) confirmed introns for skipped exons. The website contains additionally datasets used for the experiment.
AS-EAST / Alternative Splicing Effects ASsessment Tools
An online tool for the functional annotation of putative proteins encoded by transcripts generated by alternative splicing (AS). When provided with a transcript sequence, AS-EAST identifies regions altered by AS events in the putative protein sequence encoded by the transcript. Users can evaluate the predicted function of the putative protein by inspecting whether functional domains are included in the altered regions. Moreover, users can infer the loss of inter-molecular interactions in the protein network according to whether the AS events affect interaction residues observed in the 3D structure of the reference isoform. The information obtained from AS-EAST will help to design experimental analyses for the functional significance of novel splice isoforms.
TAPAS
Helps in isoform target prioritisation and experimental design. Given the biological and experimental noise associated with alternative splicing, TAPAS prioritises those splicing events that show a clear expression signal of functional importance. The TAPAS algorithm proceeds as follows. For a query isoform, it builds a cluster of isoforms from other genes (different to the query isoforms gene) whose expression patterns correlate to the query isoforms (By default Pearson similarity > 0.7), and hence could be related in the same functional module. From these proteins, a network of proteins interacting with the query isoform is built to identify clear functional links between the query isoform and other members of the cluster. The links are made up of experimental protein interactions, high confidence STRING predictions (score > 800) and highly specific GO semantic similarity links (GOSS) (default is GOSS score >6).
iRF / iterative Random Forest
Grows feature-weighted Random Forests (RF) to perform soft dimension reduction of the feature space and stabilize decision paths. iRF searches for high-order feature interactions in three steps: (i) iterative feature reweighting adaptively regularizes RF fitting, (ii) decision rules extracted from a feature-weighted RF map from continuous or categorical to binary features and (iii) a bagging step assesses the stability of recovered interactions with respect to the bootstrap-perturbation of the data.
outrigger
Uses junction reads from RNA seq data, and a graph database to create a de novo alternative splicing annotation with a graph database. Outrigger is a Python package and an RNA-seq analysis software that quantify percent spliced-in (Psi) of the events. It finds novel splicing events, including novel exons and was developed to help user to be confident in alternative exon inclusion calculations. It is recommended to use the Anaconda Python Distribution and creates an environment to install outrigger.
ASPIC / Alternative Splicing PredICtion
Obsolete
Rests on the formalization of the difficulty of detecting splice sites as an optimization problem. ASPIC provides a minimal set of transcript isoforms explaining all alternative splice events occurring among the set of transcripts considered. It contains a module for detecting and scoring splice junctions by using quality measures. Its algorithm implements a novel methodology that optimizes the overall compatibility between genomic and transcript sequences.
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