Search Results for "profile hidden markov model"
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Showing 47 open source projects for "profile hidden markov model"
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statsmodels
Statsmodels, statistical modeling and econometrics in Python
...The package is released under the open source Modified BSD (3-clause) license. Generalized linear models with support for all of the one-parameter exponential family distributions. Markov switching models (MSAR), also known as Hidden Markov Models (HMM). Vector autoregressive models, VAR and structural VAR. Vector error correction model, VECM. Robust linear models with support for several M-estimators. statsmodels supports specifying models using R-style formulas and pandas DataFrames. -
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pomegranate
Fast, flexible and easy to use probabilistic modelling in Python
pomegranate is a library for probabilistic modeling defined by its modular implementation and treatment of all models as the probability distributions they are. The modular implementation allows one to easily drop normal distributions into a mixture model to create a Gaussian mixture model just as easily as dropping a gamma and a Poisson distribution into a mixture model to create a heterogeneous mixture. But that's not all! Because each model is treated as a probability distribution, Bayesian networks can be dropped into a mixture just as easily as a normal distribution, and hidden Markov models can be dropped into Bayes classifiers to make a classifier over sequences. ... -
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Kaldi
kaldi-asr/kaldi is the official location of the Kaldi project
Kaldi is an open source toolkit for speech recognition research. It provides a powerful framework for building state-of-the-art automatic speech recognition (ASR) systems, with support for deep neural networks, Gaussian mixture models, hidden Markov models, and other advanced techniques. The toolkit is widely used in both academia and industry due to its flexibility, extensibility, and strong community support. Kaldi is designed for researchers who need a highly customizable environment to... -
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Anti-Spam SMTP Proxy Server
Anti-Spam SMTP Proxy Server implements multiple spam filters
The Anti-Spam SMTP Proxy (ASSP) Server project aims to create an open source platform-independent SMTP Proxy server which implements auto-whitelists, self learning Hidden-Markov-Model and/or Bayesian, Greylisting, DNSBL, DNSWL, URIBL, SPF, SRS, Backscatter, Virus scanning, attachment blocking, Senderbase and multiple other filter methods. Click 'Files' to download the professional version 2.8.1 build 24261. A linux(ubuntu 20.04 LTS) and a freeBSD 12.2 based ready to run OVA of ASSP V2 are also available for download. ... -
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Cerberus Content Management System 6
Cerberus Content Management System
Cerberus Content Management System is a dynamic, secure and infinitely expandable CMS designed after a Unix-Like model complete with a Unix-Like Kernel File named: Cerberus. It is a custom written Web Application Framework ( W.A.F. ) with a consistent and custom written Pre-Hyper-Text-Post-Processor Programming Code Framework ( P.C.F. ). This Web Application Software Project' aim is to be the fastest and most secure Web Application Framework, Web Application Programming Code Framework, Text,... -
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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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hiddenDomains
hiddenDomains: a modern HMM to identify ChIP-seq enrichment
hiddenDomains uses a Hidden Markov Model to identify enriched domains in ChIP-seq data. It accepts BAM files for input and can perform an analysis with or without control data. The output is a BED file, ready for the UCSC genome browser, that contains the domains and is color coded according to their posterior probabilities. -
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GPRED-GC
a Gene PREDiction model accounting for 5'-3' GC gradient
A new hidden Markov model (HMM)-based ab initio gene prediction tool for finding genes with highly variable GC contents such as the genes with negative GC gradients in grass genomes. -
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vbSPT
variational Bayes single particle tracking
vbSPT is an acronym for variational Bayes single particle tracking, a software package for hidden Markov Model analysis of single particle tracking data, primarily for biophysical applications. Journal reference: Extracting intracellular diffusive states and transition rates from single-molecule tracking data. Fredrik Persson, Martin Lindén, Cecilia Unoson & Johan Elf. Nature Methods (2013). doi:10.1038/nmeth.2367 http://www.nature.com/nmeth/journal/vaop/ncurrent/abs/nmeth.2367.html -
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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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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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Frame-Pro
HMM and directed graph consensus combing error-correction tool
Frame-Pro is a tool using Hidden Markov Model and directed acyclic graph to correct the errors in DNA sequencing reads. -
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...TagDust2 is a program to extract and correctly label the sequences to be mapped in downstream pipelines. TagDust allows users to specify the expected architecture of a read and converts it into a hidden Markov model. The latter can assign sequences to a particular barcode (or index) even in the presence of sequencing errors. Sequences not matching the architecture (primer dimers, contaminants etc.) are automatically discarded
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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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High-order HMM in Matlab
Implementation of duration high-order hidden Markov model in Matlab.
Implementation of duration high-order hidden Markov model (DHO-HMM) in Matlab with application in speech recognition. -
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The software annotates text with 41 broad semantic categories (Wordnet supersenses) for both nouns and verbs; i.e., it performs both sense disambiguation and named-entity recognition. The tagger implements a discriminatively-trained Hidden Markov Model.
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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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HMM-FRAME
Frameshift detection and correction for next-generation sequences
HMM-FRAME is designed to accurately locate and correct frameshift errors in next-generation sequencing (NGS) data using an augmented Viterbi algorithm on profile hidden Markov models (profile HMMs). By correcting the frameshift errors, it can classify more NGS sequences into their native protein domain families. -
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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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...Gene finding is done using a self-training, iterated glimmer3 analysis. The predicted genes are then analyzed for overlaps, and homology based evidence is gathered using a system of hidden markov model search and BLAST. Roles and gene symbols are assigned to the predictions based on the above analyses, common names, GO terms, and EC numbers. The genes are also translated and run through transcript level computes, including a COG analysis, motif finding, and peptide signal identification. The pipeline produces a functionally annotated genome, including RNAs and various genome characteristics, creating a stepping stone for further analysis.
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GLProbs
GLProbs: Aligning multiple sequences adaptively
GLProbs is a simple and effective approach to improve the accuracy of multiple sequence alignment. We use a natural measure to estimate the similarity of the input sequences, and based on this measure, we align the input sequences differently. To test the effectiveness of this approach, we have implemented a multiple sequence alignment tool called GLProbs and compared its performance with a dozen leading alignment tools on three benchmark alignment databases, and GLProbs’s alignments has the... -
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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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Austrian German Voices for Festival
Austrian voices for the Festival speech synthesis system
Hidden Markov Model based voice models of Austrian German for the Festival speech synthesis system.
