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Showing 19 open source projects for "hidden"
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CPAT
RNA coding potential assessment tool
Using RNA-seq, tens of thousands of novel transcripts and isoforms have been identified (Djebali, et al Nature, 2012 , Carbili et al, Gene & Development, 2011) The discovery of these hidden transcriptome rejuvenate the need of distinguishing coding and noncoding RNA. However, Most previous coding potential prediction methods heavily rely on alignment, either pairwise alignment to search for protein evidence or multiple alignments to calculate phylogenetic conservation score (such as CPC , PhyloCSF and RNACode ). This is because most previously identified transcripts including protein coding RNA and short, housekeeping/regulatory RNAs such as snRNAs, snoRNA and tRNA are highly conserved. ... -
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MetaErg
Metagenome Annotation Pipeline
MetaErg is a stand-alone and fully automated metagenome and metaproteome annotation pipeline published at: https://www.frontiersin.org/articles/10.3389/fgene.2019.00999/full. If you are using this pipeline for your work, please cite: Dong X and Strous M (2019) An Integrated Pipeline for Annotation and Visualization of Metagenomic Contigs. Front. Genet. 10:999. doi: 10.3389/fgene.2019.00999 The instructions on configuring and running the MetaErg pipeline is available at GitHub... -
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SnowyOwl
RNA-Seq based gene prediction pipeline for fungal genomes
SnowyOwl is a gene prediction pipeline that uses RNA-Seq data to train and provide hints for the generation of Hidden Markov Model (HMM)-based gene predictions, and to evaluate the resulting models. The pipeline has been validated and streamlined by comparing its predictions to manually curated gene models in three fungal genomes, and its results show substantial increases in sensitivity and selectivity over previous gene predictions. Sensitivity is gained by repeatedly running the HMM gene predictor Augustus with varied input parameters, and selectivity by choosing the models with best homology to known proteins and best agreement to the RNA-Seq data. ... -
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Hamstr
A tool for directed ortholog search in ESTs and proteins
HaMStR has moved to https://github.com/bionf/hamstr where it is now part of the HaMStR-OneSeq package. HaMStR is a profile hidden Markov model based tool for a directed ortholog search in EST or protein sequence data. The program takes a pre-defined core group of orthologous sequences (core orthologs) and a set of sequences from a search taxon as input. HaMStR then combines in a two-step strategy a pHMM based search and a reverse search via BLAST to extend the core ortholog group with novel sequences from the search taxon. -
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The General Hidden Markov Model Library (GHMM) is a C library with additional Python bindings implementing a wide range of types of Hidden Markov Models and algorithms: discrete, continous emissions, basic training, HMM clustering, HMM mixtures.
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mCarts
A hidden Markov model to predict clustered RNA motif sites
Many RBPs recognize very short and degenerate sequences, with targeting specificity achieved by mechanisms such as synergistic binding to multiple clustered sites and modulation of site accessibility through different RNA-secondary structures. mCarts integrates the number and spacing of individual motif sites, their accessibility and conservation, which substantially improves signal to noise ratio. This algorithm learns and quantifies rules of these features, taking advantage of a large... -
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TransGeneScan
TransGeneScan is a gene finding tool for metatranscriptomic sequences
...TransGeneScan is no longer maintained in SourceForge. Please find the latest version in Github. TransGeneScan is a gene finding tool for Metatranscriptomic sequences. TransGeneScan incorporates strand-speci c hidden states, representing coding sequences in sense and anti-sense strands on transcripts in a Hidden Markov Model similar to the one used in FragGeneScan (http://fraggenescan.sourceforge.net/), and can predict a sense transcript containing one or multiple genes (in an operon) or an antisense transcript. -
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MetaDomain
Protein domain classification for short sequences
MetaDomain is a protein domain classification tool designed for very short next-generation sequencing reads. It achieves better sensitivity and low false positive rate compared with the state-of-the-art profile hidden Markov model (profile HMM) alignment tool in identifying encoded domains from short sequences. -
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...It uses approximate string matching technique and protein domain analysis to detect intact LTR retrotransposons. In addition, it identifies partially deleted or solo LTRs using profile Hidden Markov Models (pHMMs). MGEScan-non-LTR is a software for the identification of non-LTR retrotransposons in genomic sequences, following a computational approach inspired by a generalized hidden Markov model (GHMM). References: 1. M. Rho et al., "De novo identification of LTR retrotransposons in eukaryotic genomes", BMC Genomics (2007) 8:90. 2. ...
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Protdraw
Create portable, flexible domain drawings of protein sequences
...ProtDraw creates flexible, easily-interpretable and portable illustrations of the domain structures of input sequences. ProtDraw is accompanied by makeProtDraw, a helper program which runs hmmer3 on a specified set of hidden Markov models and formats results for ProtDraw. Highest-scoring domains are selected in cases of overlap. Domain drawings may be organized by sequence classification. -
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ConoSorter
A Large-scale Cone Snail Transcriptome/Proteome Analysis Program
ConoSorter is a high-throughput standalone program that implements regular expressions and profile Hidden Markov Models (pHMMs) for large-scale identification and classification of precursor conopeptides into gene superfamilies and classes based on the ER signal, pro-, and mature conopeptide regions generated from raw next-generation transcriptomic or proteomic data. ConoSorter also generates a set of relevant additional information (frequency of protein sequences, length, number of cysteine residues, hydrophobicity rate of N-terminal region) and automatically searches ConoServer database to allow the user to assess the reliability and relevance of the results and to aid the identification of new conopeptide superfamilies and classes. -
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segment
Solve the Viterbi algorithm in a data stream
It is often necessary to assign a series of discrete values to continuosly variable data sequenced by time, position, etc., thereby parsing the data into fewer and larger segments of variable width. The 'segment' utility takes an input data stream as a Hidden Markov Model and applies the Viterbi algorithm to find the most likely segmentation path through the data. -
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EvoPromoter is a JAVA application that detects promoter regions in aligned nucleotide sequences using phylogenetic hidden markov models.
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ESMERALDA is a development environment for statistical recognizers operating on sequential data (speech, handwriting, biological sequences). It supports continuous density Hidden Markov models, Markov chain (N-gramm) models, and Gaussian mixture models.
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RefineHMM refines an original hidden Markov model (HMM) to find an optimal fit against the evolutionary group that the HMM models, and it does this using through iterative database searches and incremental subsequent adaptation of the seed set.
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D-finder is a bioinformatic search algorithm for the identification of D-sites in JNK interacting proteins. The algorithm is a combination of pattern matching and a hidden markov model (HMM) based on a training set of known JNK D-sites.
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hmm2gviz is a tool used for converting hidden Markov models generated by HMMER into a graph visualization using Graphviz.
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HmmSDK is a hidden Markov model (HMM) software development kit written in Java. It consists of core library of HMM functions (Forward-backward, Viterbi, and Baum-Welch algorithms) and toolkits for application development.
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