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Splice Site Recognition Using Lower Dimensional LHMM Features and SVM Classifier

Sejal Sahu
2017 International Journal for Research in Applied Science and Engineering Technology  
With an objective to further develop an efficient algorithm, Splice site recognition using lower dimensional Linear Hidden Markov Model (LHMM) features have been proposed in this paper.  ...  At present, there are several algorithms available for splice site recognition with an aim to improve the prediction accuracy.  ...  Hidden Markov Models (HMM) have been applied successfully in various applications, viz. Speech recognitions [11] .  ... 
doi:10.22214/ijraset.2017.11315 fatcat:o2kksdrvbfcebj6fyly5duuql4

A comparative genomic method for computational identification of prokaryotic translation initiation sites

M. Walker
2002 Nucleic Acids Research  
Our framework employs a product hidden Markov model (PROD-HMM) with state architecture to model the species-speci®c trinucleotide frequency patterns in sequences immediately upstream and downstream of  ...  Depending on the intricacy of the features modeled by the hidden state architecture, intergenic, regulatory, promoter and coding regions can be delimited by this method.  ...  We propose a new probabilistic method for prokaryotic genome annotation. The method employs a novel product hidden Markov model (PROD-HMM).  ... 
doi:10.1093/nar/gkf423 pmid:12136100 pmcid:PMC135744 fatcat:7acsgn2nkjft7ommwsretzxvre

Hidden Markov models from molecular dynamics simulations on DNA

K. M. Thayer, D. L. Beveridge
2002 Proceedings of the National Academy of Sciences of the United States of America  
National Academy of Sciences is collaborating with JSTOR to digitize, preserve and extend access to  ...  JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive.  ...  re] as described below. se( Hidden Markov Models.  ... 
doi:10.1073/pnas.132148699 pmid:12072566 pmcid:PMC124344 fatcat:atolfhnjt5dkjphi3s6kb2fweu

COMPUTATIONAL IDENTIFICATION OF PROMOTER REGIONS IN PROKARYOTES AND EUKARYOTES

Sudheer Menon, Shanmughavel Piramanayakam, Gopal Agarwal
2021 EPRA International Journal of Agriculture and Rural Economic Research  
In the post-genomics era, the availability of data makes it possible to build computational models to detect promoters robustly, because these models are expected to be helpful to academia and drug discovery  ...  and prokaryotic promoters.  ...  [14] In this article, the author shows that the hidden Markov model can learn the sequential structure that exists in both prokaryotic and eukaryotic promoter sequences.  ... 
doi:10.36713/epra7667 fatcat:wxqohvs3bbhftjv6gqkh7br4lq

DNA Structural Properties in the Classification of Genomic Transcription Regulation Elements

Pieter Meysman, Kathleen Marchal, Kristof Engelen
2012 Bioinformatics and Biology Insights  
This review is meant to provide an overview of the key aspects of these DNA conformational and physicochemical properties.  ...  Eg, a higher-order dinucleotide sequence model is able to account for the dependency between two sequential base pairs.  ...  The McPromoter method does this by dividing the promoter into smaller regions and models the average of the structural profiles in every segment as a single observation from a Hidden Markov Model. 61  ... 
doi:10.4137/bbi.s9426 pmid:22837642 pmcid:PMC3399529 fatcat:qfodptjuyzaofpsotbk7qsamy4

Prediction of Genomic Functional Elements

Steven J.M. Jones
2006 Annual review of genomics and human genetics (Print)  
As the number of sequenced genomes increases, the ability to deduce genome function becomes increasingly salient.  ...  Recent methodologies for predicting noncoding RNA genes, including microRNA genes and their targets, are also reviewed.  ...  In 1997 GENSCAN was published (26) and showed a significant improvement in gene prediction over the existing methods, using a generalized hidden Markov model to generate the gene structures.  ... 
doi:10.1146/annurev.genom.7.080505.115745 pmid:16824019 fatcat:ej3lgrqehvekxom736ekx6ob4m

Markov models of genome segmentation

Vivek Thakur, Rajeev K. Azad, Ram Ramaswamy
2007 Physical Review E  
Higher-order Markov models are more sensitive to the details of local patterns and in application to genome analysis, this makes it possible to segment a sequence at positions that are biologically meaningful  ...  We introduce Markov models for segmentation of symbolic sequences, extending a segmentation procedure based on the Jensen-Shannon divergence that has been introduced earlier.  ...  R.R. would like to acknowledge the hospitality of the Institute for Advanced Study, Princeton, where this work was begun.  ... 
doi:10.1103/physreve.75.011915 pmid:17358192 fatcat:tqzcfbgyyvdlvh3ki7de6npfwa

The future of transposable element annotation and their classification in the light of functional genomics - what we can learn from the fables of Jean de la Fontaine?

Peter Arensburger, Benoît Piégu, Yves Bigot
2016 Mobile Genetic Elements  
Our hope is to encourage the formation of a society to organize a larger debate on these questions and to promote the adoption of standards for annotation and an improved TE classification.  ...  Today, whole genome TE annotation is mostly done using tools that were developed to aid gene annotation rather than to specifically study TEs.  ...  The authors of RepeatMasker have attempted to address the third problematic issue (very divergent repeats) by introducing Dfam 11 which uses hidden Markov models and sequence alignments instead of simple  ... 
doi:10.1080/2159256x.2016.1256852 pmid:28090383 pmcid:PMC5160393 fatcat:mq56vw6f6jaxniziizayx7zdxq

Mycological Assessment of Deteriorated Lycopersicum esculentum Fruits Sold in Wukari Nigeria

Ogodo A. C., Agwaranze D. I., Kalu A. C., Sabo I. A., Aso R. E., Okachi M. A.
2020 Journal of Biotechnology Research  
Some of these organisms are known to be human pathogens, hence care must be taken when handling and using deteriorated tomatoes to avoid infections from these organisms.  ...  However, high water content makes them more prone to microbial attack especially spoilage by fungi.  ...  The promoter prediction is based on PWM models and Hidden Markov Models (HMM) of motifs (-35 and -10 regions).  ... 
doi:10.32861/jbr.67.84.89 fatcat:qkblhkjxyrgfbk6rtdj24zokre

Hybrid Approach Using SVM and MM2 in Splice Site Junction Identification

Srabanti Maji, Deepak Garg
2014 Current Bioinformatics  
Hence, an efficient method, MM2F-SVM is proposed through this article, which consists of three stages -initial stage, in which a second order Markov Model (MM2) is used, i.e. feature extraction; intermediate  ...  Therefore, the algorithms used in the splice sites identification must be improved in order to recover the prediction accuracy.  ...  ACKNOWLEDGEMENTS The authors are grateful to the anonymous reviewers, Prof. Sanghamitra Bandyopadhyay, Machine Intelligence Unit, Indian Statistical Institute, Kolkata and Prof.  ... 
doi:10.2174/1574893608999140109121721 fatcat:lc37zxp55je65bybzgwwsncsyu

Comprehensive identification and quantification of microbial transcriptomes by genome-wide unbiased methods

Ulrike Mäder, Pierre Nicolas, Hugues Richard, Philippe Bessières, Stéphane Aymerich
2011 Current Opinion in Biotechnology  
Providing comprehensive identification and quantification of transcripts with an unprecedented resolution, they are leading to major breakthroughs in systems biology.  ...  Methodological requirements and statistical frameworks are often similar in both the approaches despite differences in the nature of the data.  ...  The idea has been successfully employed for tiling array data, from simple piecewise-constant regression [42,43 ,44 ] to more sophisticated hidden Markov models which integrate signal drifts [45 ] .  ... 
doi:10.1016/j.copbio.2010.10.003 pmid:21074401 fatcat:5nzupyyb4rfipah6mt67jiashm

Mosaic origin of the eukaryotic kinetochore

Eelco C. Tromer, Jolien J. E. van Hooff, Geert J. P. L. Kops, Berend Snel
2019 Proceedings of the National Academy of Sciences of the United States of America  
While prokaryotes operate simple systems to connect DNA to the segregation machinery during cell division, eukaryotes use a highly complex protein assembly known as the kinetochore.  ...  The emergence of eukaryotes from ancient prokaryotic lineages embodied a remarkable increase in cellular complexity.  ...  We are indebted to the members of the G.J.P.L.K. and B.S. labs for helpful discussions on the research.  ... 
doi:10.1073/pnas.1821945116 pmid:31127038 pmcid:PMC6601020 fatcat:aan7jalhyfha7jjwq2mbjkend4

Computational Identification of Novel Genes: Current and Future Perspectives

Steffen Klasberg, Tristan Bitard-Feildel, Ludovic Mallet
2016 Bioinformatics and Biology Insights  
Their discovery called for an extension of the historical hypotheses about gene origination.  ...  Computational approaches are further prime methods that can be based on existing models or leveraging biological evidences from experiments.  ...  by probabilistic models, namely, hidden Markov models (HMMs).  ... 
doi:10.4137/bbi.s39950 pmid:27493475 pmcid:PMC4970615 fatcat:6rbtbdxmf5hz5nthw6hgesrl3m

An integrative computational approach to effectively guide experimental identification of regulatory elements in promoters

Igor V Deyneko, Siegfried Weiss, Sara Leschner
2012 BMC Bioinformatics  
We apply it to promoters that drive tumor-specific gene expression in tumor-colonizing Gram-negative bacteria.  ...  Conclusions: Experimental analysis of promoter structures guided by bioinformatics has proved to be efficient.  ...  Hidden Markov Model prediction shows lower specificity (C TSS + = 0.83, C TSS -= 0.43).  ... 
doi:10.1186/1471-2105-13-202 pmid:22897887 pmcid:PMC3465240 fatcat:6dtgu3qe7rgvvlejhvq3jsmkwy

MRFy: Remote Homology Detection for Beta-Structural Proteins Using Markov Random Fields and Stochastic Search

Noah M. Daniels, Andrew Gallant, Norman Ramsey, Lenore J. Cowen
2015 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
Menke, Berger, and Cowen proposed a Markov random field model to predict remote homology for beta-structural proteins, but their formulation was computationally intractable on many beta-strand topologies  ...  An automatic computational method reasonably approximates a human-curated hierarchical organization of proteins according to their degree of homology.  ...  [KBM + 94] used HMMs to model protein evolution.1.3.1 Profile Hidden Markov ModelsWith respect to homology detection, profile hidden Markov models have been popular.  ... 
doi:10.1109/tcbb.2014.2344682 pmid:26357074 fatcat:6wo3cmou5jcqdhd4bm7hpm634m
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