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Novel Phylogenetic Network Inference by Combining Maximum Likelihood and Hidden Markov Models [chapter]

Sagi Snir, Tamir Tuller
Lecture Notes in Computer Science  
The model describes the phylogenetic network as a Hidden Markov Model (HMM), where each hidden state is related to one of the network's trees.  ...  In this work we suggest a new probabilistic model for analyzing and modeling phylogenetic networks, the NET-HMM.  ...  Acknowledgment T.T. was supported by the Edmond J. Safra Bioinformatics program at Tel Aviv University.  ... 
doi:10.1007/978-3-540-87361-7_30 fatcat:e4pd4gtfujd2ze6eigbmpcqg6e

THE NET-HMM APPROACH: PHYLOGENETIC NETWORK INFERENCE BY COMBINING MAXIMUM LIKELIHOOD AND HIDDEN MARKOV MODELS

SAGI SNIR, TAMIR TULLER
2009 Journal of Bioinformatics and Computational Biology  
The model describes the phylogenetic network as a Hidden Markov Model (HMM), where each hidden state is related to one of the network's trees.  ...  In this work we suggest a new probabilistic model, the NET-HMM, for analyzing and modeling phylogenetic networks.  ...  Acknowledgment T.T. was supported by the Edmond J. Safra Bioinformatics Program at Tel Aviv University and the Yeshaya Horowitz Association through the Center for Complexity Science.  ... 
doi:10.1142/s021972000900428x pmid:19634195 fatcat:ss6qxsre5bcwtbjk6t62n6vgbq

Pathway Modeling: New face of Graphical Probabilistic Analysis

Somnath Tagore, Virendra S. Gomase, Rajat K. De
2008 Journal of Proteomics & Bioinformatics  
Graphical probabilistic approaches are one of the unique methodologies that are used for designing and analyzing pathways.  ...  Modeling biological pathways is interesting as well as difficult to optimize. Various modeling problems of diseases can be successfully analyzed using this simulation approach.  ...  Maximum Likelihood is used in phylogenetic estimates, study genetic cross-over, pathway modeling and gene expression analysis.  ... 
doi:10.4172/jpb.1000035 fatcat:jcoxyyn3bfh6zhd3zhauwq6rhu

A Perspective of Conventional and Bio-inspired Optimization Techniques in Maximum Likelihood Parameter Estimation

Yongzhong Lu, Min Zhou, Shiping Chen, David Levy, Jicheng You
2018 Journal of Autonomous Intelligence  
Maximum likelihood estimation is a method of estimating the parameters of a statistical model in statistics.  ...  This review paper attempts to offer a comprehensive perspective of conventional and bio-inspired optimization techniques in maximum likelihood parameter estimation so as to highlight the challenges and  ...  Acknowledgments This work is partly supported by the Fundamental Research Funds for the Central Universities in China (HUST: 2016YXMS105).  ... 
doi:10.32629/jai.v1i2.28 fatcat:7hfsl4shkjbpvggyvydwgv2lle

Efficient approximations for learning phylogenetic HMM models from data

V. Jojic, N. Jojic, C. Meek, D. Geiger, A. Siepel, D. Haussler, D. Heckerman
2004 Bioinformatics  
Unfortunately, computing the likelihood of phylogenetic-HMM models is intractable.  ...  In particular, we consider a general probabilistic model described in Siepel and Haussler that we call the phylogenetic-HMM model which generalizes the classical probabilistic models of Neyman and Felsenstein  ...  In Section 2, we describe phylogenetic-HMM models in terms of Bayesian networks or DAG models.  ... 
doi:10.1093/bioinformatics/bth917 pmid:15262795 fatcat:4vxechrwlnh6pcczxdwfhomksi

Detection of Recombination in DNA Multiple Alignments with Hidden Markov Models

Dirk Husmeier, Frank Wright
2001 Journal of Computational Biology  
Key words: phylogenetic trees, multiple alignments of DNA sequences, recombination, hidden Markov models, maximum likelihood and the expectation maximization (EM) algorithm.  ...  DETECTION OF RECOMBINATION 403 due to recombination with a hidden Markov model (HMM).  ...  ACKNOWLEDGMENTS This work was funded by the Biotechnology and Biological Sciences Research Council (BBSRC) Bioinformatics Initiative and the Scottish Executive Rural Affairs Department (SERAD).  ... 
doi:10.1089/106652701752236214 pmid:11571075 fatcat:4h5i22k3nva5jc2zpsgtob4uwm

Phylogenetic systematics turns over a new leaf

Paul O. Lewis
2001 Trends in Ecology & Evolution  
Long restricted to the domain of molecular systematics and studies of molecular evolution, likelihood methods are now being used in analyses of discrete morphological data, specifically to estimate ancestral  ...  Biologists are beginning to apply likelihood models within a Bayesian statistical framework, which promises not only to provide answers that evolutionary biologists desire, but also to make practical the  ...  Lewis, Mark Pagel, Chris Simon and Ziheng Yang for their careful reading of earlier drafts of this article. I also gratefully acknowledge the Alfred P.  ... 
doi:10.1016/s0169-5347(00)02025-5 pmid:11146142 fatcat:nzirg2ymrvfeznnsavt7hvz7s4

Ancestral reconstruction of protein interaction networks

Benjamin J. Liebeskind, Richard W. Aldrich, Edward M. Marcotte, Maricel G Kann
2019 PLoS Computational Biology  
We deploy this new framework to infer the ancestral states and evolutionary dynamics of protein-interaction networks by analyzing >16,000 predominantly metazoan co-fractionation and affinity-purification  ...  molecular data, and develop a new parameterization and fitting strategy that is useful for comparative inference of biochemical networks.  ...  modeling framework and the Texas Advanced Computing Center at the University of Texas for high-performance computing resources.  ... 
doi:10.1371/journal.pcbi.1007396 pmid:31658251 pmcid:PMC6837550 fatcat:sgmvzzebx5hhzoxjo3guontk7e

Models of coding sequence evolution

W. Delport, K. Scheffler, C. Seoighe
2008 Briefings in Bioinformatics  
These models have become increasingly sophisticated and combined with statistical model comparison techniques have helped to shed light on how genes and proteins evolve.  ...  Probabilistic models of sequence evolution are in widespread use in phylogenetics and molecular sequence evolution.  ...  The combination of hidden Markov models to model rate variation along the sequence and phylogenetic models describing sequence evolution across taxa was introduced to model autocorrelation of evolutionary  ... 
doi:10.1093/bib/bbn049 pmid:18971241 pmcid:PMC2638624 fatcat:pokp3ypkszfunjftblwlaoxmji

Advances in Computational Methods for Phylogenetic Networks in the Presence of Hybridization [article]

R.A.L. Elworth, H.A. Ogilvie, J. Zhu, L. Nakhleh
2018 arXiv   pre-print
Phylogenetic networks extend phylogenetic trees to allow for modeling reticulate evolutionary processes such as hybridization.  ...  In particular, parsimony, likelihood, and Bayesian methods have been devised for estimating phylogenetic networks and associated parameters using estimated gene trees as data.  ...  While the approaches pursued at the time were basic, they were foundational in terms of pursuing more sophisticated models and approaches by Nakhleh and his group.  ... 
arXiv:1808.08662v1 fatcat:par4fybfkrdu5m4bfiunqgs4xm

Likelihood-Based Inference of Phylogenetic Networks from Sequence Data by PhyloDAG [chapter]

Quan Nguyen, Teemu Roos
2015 Lecture Notes in Computer Science  
Processes such as hybridization, horizontal gene transfer, and recombination result in reticulation which can be modeled by phylogenetic networks.  ...  Earlier likelihood-based methods for inferring phylogenetic networks from sequence data have been encumbered by the computational challenges related to likelihood evaluations.  ...  The anonymous reviewers suggested a comparison to the PhyloNet method and made several other suggestions that significantly improved the paper.  ... 
doi:10.1007/978-3-319-21233-3_10 fatcat:7jas5a7flfdjvhvressyuwnswi

Ancestral Reconstruction of Protein Interaction Networks [article]

Benjamin Liebeskind, Richard W Aldrich, Edward M. Marcotte
2018 bioRxiv   pre-print
We deploy this new framework to infer the ancestral states and evolutionary dynamics of protein-interaction networks by analyzing >16,000 predominantly metazoan co-fractionation and affinity-purification  ...  molecular data, and develop a new parameterization and fitting strategy that is useful for comparative inference of biochemical networks.  ...  In general, fitting the model by maximum likelihood performed poorly by this measure on both training and test data (Figure 3A ). We then tried fitting the model using the APS itself as a criterion.  ... 
doi:10.1101/408773 fatcat:ow2ld4oty5gdrdncemjxaguom4

Stochastic models of sequence evolution including insertion—deletion events

István Miklós, Ádám Novák, Rahul Satija, Rune Lyngsø, Jotun Hein
2009 Statistical Methods in Medical Research  
Comparison of sequences that have descended from a common ancestor based on an explicit stochastic model of substitutions, insertions and deletions has risen to prominence in the last decade.  ...  Besides the computational challenges, increasing realism in the underlying models is presently being addressed.  ...  Acknowledgements This work was supported by BBSRC grant BB/C509566/1. I.M. was also supported by a Bolyai postdoctoral fellowship and an OTKA grant F 61730.  ... 
doi:10.1177/0962280208099500 pmid:19221170 fatcat:qu7i5gvy3zawjfap3kyghjarla

Hidden Markov Models for Evolution and Comparative Genomics Analysis

Nadezda A. Bykova, Alexander V. Favorov, Andrey A. Mironov, Liran Carmel
2013 PLoS ONE  
Citation: Bykova NA, Favorov AV, Mironov AA (2013) Hidden Markov Models for Evolution and Comparative Genomics Analysis. PLoS ONE 8(6): e65012.  ...  The main idea is formulation of the problem as a hidden Markov model on a tree (tree HMM, tHMM), where the basic continuous-time Markov model is expanded with the introduction of emission probabilities  ...  Acknowledgments The authors thank Mikhail Gelfand and Eugene Leushkin for fruitful discussions, and Pavel Novichkov for sharing the CRP data.  ... 
doi:10.1371/journal.pone.0065012 pmid:23762278 pmcid:PMC3676395 fatcat:lcohneuvavgmbafyfxfhkoo6mi

Algebraic Statistics in Practice: Applications to Networks

Marta Casanellas, Sonja Petrović, Caroline Uhler
2017 Annual Review of Statistics and Its Application  
In this review, we illustrate this on three problems related to networks: network models for relational data, causal structure discovery, and phylogenetics.  ...  For each problem, we give an overview of recent results in algebraic statistics, with emphasis on the statistical achievements made possible by these tools and their practical relevance for applications  ...  Algebraic approaches to phylogenetics avoid parameter inference altogether and make phylogenetic inference feasible for the most general Markov model, the GMM.  ... 
doi:10.1146/annurev-statistics-031017-100053 fatcat:cmd2g7mbhzgbxpp4erqzf5klfu
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