Search Results for "hidden markov java" - Page 3
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Showing 133 open source projects for "hidden markov java"
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jnostromo
E-Sport Drivers for the Razer Nostromo
Deprecated - please use Keyboarding Master: https://sites.google.com/site/keyboardingmaster/ jnostromo provides drivers for the Razer Nostromo & Belkin N52/N52te designed to be E-Sport legal. Profiles are unique user defined keymappings and can be created for each game. Each profile can have up to 8 unique keymaps with mappings to switch between keymaps. jnostromo includes an easy to use configuration gui to map keys from the nostromo to the keyboard and/or mouse. The... -
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Electro-Mechanical Computer Simulation
An electromechanical computer simulation.
This project is a simulation of an electromechanical computer based upon the design presented in Charles Petzold's book "CODE: The Hidden Language of Computer Hardware and Software" -
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CrypPic is a free software application based on Java 8 which can be used to encrypt and manipulate the image.
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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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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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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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vbTPM
Variational Bayes for tethered particle motion
vbTPM is an analysis package aimed at analyzing time series from a single molecule technique called tethered particle motion, which are common for in vitro investigations of protein-nucleic acid interactions. vbTPM uses a variational approach to hidden Markov models, and resembles recent methods for single molecule FRET (http://vbfret.sourcefore.net/) and single particle tracking (http://vbspt.sourceforge.net/) data. 2014-08-12: NAR manuscript in print! http://dx.doi.org/10.1093/nar/gku563 2014-06-11: manuscript accepted for publication in Nucleic Acids Research. Preprint: http://arxiv.org/abs/1402.0894 If you use this code, please cite our work: Stephanie Johnson, Jan-Willem van de Meent, Rob Phillips, Chris H. ... -
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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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DJVUEd
GUI for editing djvu files metadata
GUI for editing djvu files metadata. Can help avoid some mistakes during editing annotations, oulines, hidden text and naming pages. Based on djvused program from DjVuLibre package. -
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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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MRHMMs
multivariate regression hidden Markov models
It includes a various hidden Markov models: regression, logistic regression, hidden Markov models, and emission probability density of a mixture of multivariate Normal distributions. Also available at https://github.com/yonoklee/MRHMMs Work in progress (Jun 20, 2021 - ) -
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High-order HMM in Java
A duration high-order hidden Markov model (DHO-HMM) in Java.
This project provides an implementation of duration high-order hidden Markov model (DHO-HMM) in Java. It is compactible with JDK 5 & 6. It was used in the author's research on speech recognition of Mandarin digits. There are some Chinese words in this project and I am afraid that I don't have enough time to translate to English recently. -
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Electronic Data Tags
Electronic Data Tags value storage API For java.
EDT is an API For java designed to allow you to store data from your programs in files easily. EDT is separated into two parts: EDT Basic (just called EDT) and EDTA (Advanced). EDT Basic stores only String values, while EDTA uses EDT Basic to store String, int, boolean, float, long, double, and byte values. To make accessing values easier, EDT and EDTA allow you to assign a name, like "FileLocation", to a value, instead of an integer, like in an array. The values are stored as ISO-8859-1 Strings. -
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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. -
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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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HYDRA is an open-source, platform-neutral library for performing Markov Chain Monte Carlo. It implements the logic of standard MCMC samplers within a framework designed to be easy to use and to extend while allowing integration with other software to
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HMM Speech Recognition in Matlab
A speech recognition system using Matlab/Simulink/Stateflow.
This project provide hidden Markov model speech recognition system by using Matlab/Simulink/Stateflow. -
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QuasiRecomb
Probabilistic inference of viral Quasispecies
...This population, shaped by the combination of genetic change and selection, is called quasispecies. Genetic change is due to both point mutations and recombination events. We present a jumping hidden Markov model that describes the generation of the viral quasispecies and a method to infer its parameters by analysing next generation sequencing data. We offer an implementation of the EM algorithm to find maximum a posteriori estimates of the model parameters and a method to estimate the distribution of viral strains in the quasispecies. ... -
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CGI-HMM
Find CpG island by HMM
Find CpG island for whole genome/chromosome by Hidden-Markov Mode -
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HPeak
A HMM-based algorithm for defining enriched regions from ChIP-seq data
HPeak is a hidden Markov model-based approach that can accurately pinpoint regions to where significantly more sequence reads map. Testing on real data shows that these regions are indeed highly enriched by the right protein binding sites. Command (single-end): perl /compbio/software/HPeak3/HPeak.pl -sp HUMAN/MOUSE -format BED -t TREATMENT.inp -c CONTROL.inp -n OUTPUTPREFIX -fmin 100 -fmax 300 -r 36 -ann -wig -seq -interfiles Command (pair-end): perl /compbio/software/HPeak3/HPeak.pl -sp HUMAN/MOUSE -format BED -pe TREATMENT.inp -c CONTROL.inp -n OUTPUTPREFIX -isize 200 -r 100 -pec (if control is PE) -ann -wig -seq –interfiles note: 1. ... -
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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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JaCHMM
Java Conditioned Hidden Markov Model library
The JaCHMM - the Java Conditioned Hidden Markov Model library - is a complete implementation of a CHMM in Java ready to use either on command line or as a module. The JaCHMM is licenced under the BSD licence. It gives an implementation of the Viterbi, Forward-Backward, Baum-Welch and K-Means algorithms, all adapted for the CHMM. JaCHMM is based on the JaHMM and also designed to achieve reasonable performance without making the code unreadable. -
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JProGraM (PRObabilistic GRAphical Models in Java) is a statistical machine learning library. It supports statistical modeling and data analysis along three main directions: (1) probabilistic graphical models (Bayesian networks, Markov random fields, dependency networks, hybrid random fields); (2) parametric, semiparametric, and nonparametric density estimation (Gaussian models, nonparanormal estimators, Parzen windows, Nadaraya-Watson estimator); (3) generative models for random networks (small-world, scale-free, exponential random graphs, Fiedler random fields), subgraph sampling algorithms (random walk, snowball, etc.), and spectral decomposition.
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SRM2 Sound Recognizer Mobile 2
A Sound Recognition Framework developed to J2ME plataform
The SRM Framework 2 was developed for the J2ME platform supporting sound recognition dependent and speaker-independent, through the recognition techniques DTW (Dynamic Time Warping) and HMM (Hidden Markov Models), in addition to providing support to the import and export of data any stage of recognition enabling the use of external resources as well as the tool running steps on remote terminals. It has the following characteristics: - DTW - HMM (Discrete Models) - Suports Sound in PCM - Vector quantization using the k-means algorithm - Uses the algorithm Forward - Uses the algorithm Backward - Uses the Viterbi algorithm - Uses the Baum-Welch algorithm for training - Has features import and export data Further information is on Gaita 2012.
