• R/qtl

  • Referenced in 13 articles [sw20451]
  • accessible and allow users to focus on modeling rather than computing. A key component ... methods for QTL mapping is the hidden Markov model (HMM) technology for dealing with missing...
  • hmmm

  • Referenced in 12 articles [sw07947]
  • proposed by Lang (2004) and (2005); hidden Markov models where the distribution of the observed...
  • Infernal

  • Referenced in 12 articles [sw17000]
  • structure of an RNA family called covariance models (CMs) from structurally annotated multiple sequence alignments ... homology search based on accelerated profile hidden Markov model (HMM) methods and HMM-banded...
  • momentuHMM

  • Referenced in 8 articles [sw21676]
  • momentuHMM: R package for generalized hidden Markov models of animal movement. Discrete-time hidden Markov...
  • VanillaICE

  • Referenced in 6 articles [sw11310]
  • VanillaICE. A Hidden Markov Model for high throughput genotyping arrays. Bioconductor. Hidden Markov Models ... VanillaICE contains the software for fitting hidden Markov models on genomic array data to infer...
  • SLAM

  • Referenced in 5 articles [sw17327]
  • alignment with a generalized pair hidden Markov model. Comparative-based gene recognition is driven ... probabilistic framework is the generalized pair hidden Markov model, a hybrid of (1) generalized hidden ... gene finding, and (2) pair hidden Markov models, which have applications to sequence alignment...
  • SRN/HMM

  • Referenced in 9 articles [sw02952]
  • simple recurrent network(SRN) and the hidden Markov models(HMM) are combined in this approach...
  • MCINTYRE

  • Referenced in 8 articles [sw22925]
  • increasing attention for its ability to model domains with complex and uncertain relations among entities ... biological networks, artificial datasets and a hidden Markov model. MCINTYRE is compared with the Monte...
  • KinasePhos

  • Referenced in 8 articles [sw22468]
  • previous work, KinasePhos 1.0, incorporated profile hidden Markov model (HMM) with flanking residues...
  • GenRGenS

  • Referenced in 7 articles [sw09070]
  • sequence analysis, such as Markov chains, hidden Markov models, weighted context-free grammars, regular expressions...
  • SUPERFAMILY

  • Referenced in 5 articles [sw16889]
  • based on a collection of hidden Markov models, which represent structural protein domains ... completely sequenced genomes against the hidden Markov models...
  • Torchvision

  • Referenced in 5 articles [sw27285]
  • Networks, Support Vector Machines, Gaussian Mixture Models, Hidden Markov Models and many others. Torchvision provides...
  • HHpred

  • Referenced in 7 articles [sw17271]
  • implement pairwise comparison of profile hidden Markov models (HMMs). It allows to search a wide...
  • EasyGene

  • Referenced in 7 articles [sw17322]
  • gene finder is based on a hidden Markov model (HMM) that is automatically estimated...
  • GeneScout

  • Referenced in 7 articles [sw31815]
  • system contains specially designed hidden Markov models (HMMs) for detecting functional sites including protein-translation...
  • hmm.discnp

  • Referenced in 4 articles [sw11735]
  • hmm.discnp: Hidden Markov models with discrete non-parametric observation distributions. Fits hidden Markov models with ... Simulates data from such models. Finds most probable underlying hidden states, the most probable sequences...
  • mhsmm

  • Referenced in 7 articles [sw19752]
  • package mhsmm: Inference for Hidden Markov and Semi-Markov Models. Parameter estimation and prediction ... hidden Markov and semi-Markov models for data with multiple observation sequences. Suitable for equidistant...
  • GeneMarkS

  • Referenced in 6 articles [sw23024]
  • near gene start within an iterative Hidden Markov model based algorithm. The new gene prediction...
  • HMM

  • Referenced in 4 articles [sw11733]
  • package HMM: HMM - Hidden Markov Models. Easy to use library to setup, apply and make ... with discrete time and discrete space Hidden Markov Models...
  • HMMmix

  • Referenced in 4 articles [sw13500]
  • Hidden Markov models with mixtures as emission distributions. In unsupervised classification, Hidden Markov Models ... parametric family. In this paper, a semiparametric model where the emission distributions are a mixture ... algorithm can be adapted to infer the model parameters. For the initialization step, starting from ... hierarchical method to combine them into the hidden states is proposed. Three likelihood-based criteria...