JUCHMME: a Java Utility for Class Hidden Markov Models and Extensions for biological sequence analysis

Autor: Konstantinos D. Tsirigos, Panagiota I. Kontou, Zoi I. Litou, Dimitra Sarantopoulou, Georgios N. Tsaousis, Pantelis G. Bagos, Ioannis A. Tamposis, Margarita C. Theodoropoulou

Publikováno v: Tamposis, I A, Tsirigos, K D, Theodoropoulou, M C, Kontou, P I, Tsaousis, G N, Sarantopoulou, D, Litou, Z I & Bagos, P G 2020, ' JUCHMME: A Java Utility for Class Hidden Markov Models and Extensions for biological sequence analysis ', Bioinformatics, vol. 35, no. 24, pp. 5309–5312 . https://doi.org/10.1093/bioinformatics/btz533

Summary JUCHMME is an open-source software package designed to fit arbitrary custom Hidden Markov Models (HMMs) with a discrete alphabet of symbols. We incorporate a large collection of standard algorithms for HMMs as well as a number of extensions a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ddf31630d6ac4557b056f1a817806d70
https://doi.org/10.1093/bioinformatics/btz533

The human GPCR signal transduction network

Autor: Panagiota I. Kontou, Margarita C. Theodoropoulou, Georgios N. Tsaousis, Stavros J. Hamodrakas, Athanasia Pavlopoulou, Niki Dimou, Pantelis G. Bagos, Georgios A. Pavlopoulos, Georgia G. Braliou

The eukaryotic cell surface G protein-coupled receptors (GPCRs) interact with a wide spectrum of ligands. The intracellular transmission of the extracellular signal is mediated by the selective coupling of GPCRs to G proteins, which, in turn, activat

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fff1179aedaee65c9c6cb847942b8d2b
https://avesis.deu.edu.tr/publication/details/5cda7bc1-7a6c-474d-b7d6-b5c9f6acedd5/oai

Semi-supervised learning of Hidden Markov Models for biological sequence analysis

Autor: Ioannis A. Tamposis, Panagiota I. Kontou, Pantelis G. Bagos, Margarita C. Theodoropoulou, Konstantinos D. Tsirigos

Publikováno v: Bioinformatics. 35:2208-2215

Motivation Hidden Markov Models (HMMs) are probabilistic models widely used in applications in computational sequence analysis. HMMs are basically unsupervised models. However, in the most important applications, they are trained in a supervised mann

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99f2562475c983fa6962151c28035c02
https://doi.org/10.1093/bioinformatics/bty910

Alternative Splicing Detection Tool-a novel PERL algorithm for sensitive detection of splicing events, based on next-generation sequencing data analysis

Autor: Panagiotis G. Adamopoulos, Andreas Scorilas, Margarita C. Theodoropoulou

Publikováno v: Annals of translational medicine. 6(12)

Next-generation sequencing (NGS) can provide researchers with high impact information regarding alternative splice variants or transcript identifications. However, the enormous amount of data acquired from NGS platforms make the analysis of alternati

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9fda9101441e6e937949958474eb0b0c
https://pubmed.ncbi.nlm.nih.gov/30069446

Predicting Alpha Helical Transmembrane Proteins Using HMMs

Autor: Margarita C. Theodoropoulou, Pantelis G. Bagos, Georgios N. Tsaousis, Stavros J. Hamodrakas

Publikováno v: Hidden Markov Models ISBN: 9781493967513

Alpha helical transmembrane (TM) proteins constitute an important structural class of membrane proteins involved in a wide variety of cellular functions. The prediction of their transmembrane topology, as well as their discrimination in newly sequenc

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::99e58a11ec1095ada882c797f736305b
https://doi.org/10.1007/978-1-4939-6753-7_5