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Core column prediction for protein multiple sequence alignments

Dan DeBlasio, John Kececioglu
2017 Algorithms for Molecular Biology  
Results: We develop for the first time a predictor of column coreness for protein multiple sequence alignments.  ...  In a computed protein multiple sequence alignment, the coreness of a column is the fraction of its substitutions that are in so-called core columns of the gold-standard reference alignment of its proteins  ...  Availability of data and materials The benchmarks used for training and testing, as well as the original version of the Facet estimator, are available at  ... 
doi:10.1186/s13015-017-0102-3 pmid:28435440 pmcid:PMC5397798 fatcat:ggbbt3chhfe2lofg2xumj6baqu

Estimating the Accuracy of Multiple Alignments and its Use in Parameter Advising [chapter]

Dan F. DeBlasio, Travis J. Wheeler, John D. Kececioglu
2012 Lecture Notes in Computer Science  
We develop a novel and general approach to estimating the accuracy of protein multiple sequence alignments without knowledge of a reference alignment, and use our approach to address a new problem that  ...  The new approach we develop for accuracy estimation significantly improves on prior approaches, as we demonstrate through its performance on parameter advising.  ...  Suppose that for the protein sequences in a multiple alignment we have predicted the secondary structure of each protein, using a standard prediction tool such as PSIPRED [4] .  ... 
doi:10.1007/978-3-642-29627-7_5 fatcat:brfdyciiqvfbfgzm5qujmgo4uq

Adaptive Local Realignment of Protein Sequences

Dan DeBlasio, John Kececioglu
2018 Journal of Computational Biology  
While mutation rates can vary markedly over the residues of a protein, multiple sequence alignment tools typically use the same values for their scoring-function parameters across a protein's entire length  ...  This new method of local parameter advising, when combined with prior methods for global advising, boosts alignment accuracy as much as 26% over the best default setting on hard-to-align protein benchmarks  ...  Acknowledgements Research of JK and DD at the University of Arizona was supported by NSF Grant IIS-1217886 to JK.  ... 
doi:10.1089/cmb.2018.0045 pmid:29889553 pmcid:PMC6067105 fatcat:hixkki644jgy3pk7r3oyoskvvq

Boosting alignment accuracy through adaptive local realignment [article]

Dan DeBlasio, John Kececioglu
2016 bioRxiv   pre-print
Motivation: While mutation rates can vary across the residues of a protein, when computing alignments of protein sequences the same setting of values for substitution score and gap penalty parameters is  ...  Availability: A new version of the Opal multiple sequence aligner that incorporates adaptive local realignment using Facet for parameter advising, is available free for non-commercial use at  ...  Evaluating the Facet estimator on an alignment with m sequences and n columns, after secondary structure has been predicted for the protein sequences, takes Θ(m 2 n) time.  ... 
doi:10.1101/063131 fatcat:aoolblbiijgsrehdysewi2lt4a

Ensemble multiple sequence alignment via advising

Dan DeBlasio, John Kececioglu
2015 Proceedings of the 6th ACM Conference on Bioinformatics, Computational Biology and Health Informatics - BCB '15  
The multiple sequence alignments computed by an aligner for different settings of its parameters, as well as the alignments computed by different aligners using their default settings, can differ markedly  ...  Through cross-validation experiments on benchmark protein sequence alignments, we show that parameter advising boosts an aligner's accuracy beyond its default setting for virtually all of the standard  ...  ACKNOWLEDGEMENTS We thank the reviewers for their helpful comments. This work was supported by NSF Grant IIS-1217886 to J.K., and a PhD fellowship to D.D. from NSF Grant DGE-0654435.  ... 
doi:10.1145/2808719.2808766 dblp:conf/bcb/DeBlasioK15 fatcat:wybevq63qvgxzd2vzu6a5ktyum

Exploiting Large Datasets Improves Accuracy Estimation for Multiple Sequence Alignment [article]

Luis Cedillo, Hector Richart Ruiz, Dan DeBlasio
2022 bioRxiv   pre-print
One highly-accurate method of choosing parameter vectors for specific input is Parameter Advising, which selects from a set of alignments produced using a carefully constructed collection of parameter  ...  Often practitioners use software's default parameters to align sequences. However, a different parameter setting may provide a much higher-quality alignment for the specific set of input sequences.  ...  Olac Fuentes and Jose Perez for fruitful discussions and the UTEP Campus Office of Undergraduate Research Initiatives (COURI).  ... 
doi:10.1101/2022.05.22.493004 fatcat:glvy7a2wgzbg3abu6ep4yc4yia

The HHpred interactive server for protein homology detection and structure prediction

J. Soding, A. Biegert, A. N. Lupas
2005 Nucleic Acids Research  
HHpred is a fast server for remote protein homology detection and structure prediction and is the first to implement pairwise comparison of profile hidden Markov models (HMMs).  ...  It allows to search a wide choice of databases, such as the PDB, SCOP, Pfam, SMART, COGs and CDD. It accepts a single query sequence or a multiple alignment as input.  ...  We thank Sergej Djuranovic for first pointing out the HHpred prediction for the SpoVT C-terminal domain. J.S. is indebted to Alex Diemand for assistance in preparing the screenshots.  ... 
doi:10.1093/nar/gki408 pmid:15980461 pmcid:PMC1160169 fatcat:bt2u5h6subd2hb7r2eifs74eqe

Protein sequence comparison and fold recognition: progress and good-practice benchmarking

Johannes Söding, Michael Remmert
2011 Current Opinion in Structural Biology  
In combination with a domaincentered approach to function and structure prediction, modern remote homology detection methods have a great and largely underexploited potential for elucidating protein functions  ...  Advances during the last few years include nonlinear scoring functions combining various sequence features, the use of sequence context information, and powerful new software packages.  ...  We thank Julian Gough, Ceslovas Venclovas, and Jinbo Xu for comments and discussions.  ... 
doi:10.1016/ pmid:21458982 fatcat:m3xcvvmmerh6nbewcchdrd4nxy

FreeContact: fast and free software for protein contact prediction from residue co-evolution

László Kaján, Thomas A Hopf, Matúš Kalaš, Debora S Marks, Burkhard Rost
2014 BMC Bioinformatics  
20 years of improved technology and growing sequences now renders residue-residue contact constraints in large protein families through correlated mutations accurate enough to drive de novo predictions  ...  of protein three-dimensional structure.  ...  MK was supported by a grant from the Research Council of Norway (208481, ELIXIR.NO, supporting the Norwegian Bioinformatics Platform).  ... 
doi:10.1186/1471-2105-15-85 pmid:24669753 pmcid:PMC3987048 fatcat:l5b2jxuwb5hhlk342h5x2oonsq

COMPASS server for remote homology inference

R. I. Sadreyev, M. Tang, B.-H. Kim, N. V. Grishin
2007 Nucleic Acids Research  
COMPASS is a method for homology detection and local alignment construction based on the comparison of multiple sequence alignments (MSAs).  ...  To illustrate the value of this tool for protein structure-functional prediction, we present two examples of detecting distant homologs for uncharacterized protein families. Available at  ...  We would like to thank Lisa Kinch and James Wrabl for discussions and critical reading of the manuscript.  ... 
doi:10.1093/nar/gkm293 pmid:17517780 pmcid:PMC1933213 fatcat:lvc7yqucfzec3oqgnstoh67b7m

Whole-Genome Annotation with BRAKER [chapter]

Katharina J. Hoff, Alexandre Lomsadze, Mark Borodovsky, Mario Stanke
2019 Msphere  
GeneMark-ES/ET learns its parameters from a novel genomic sequence in a fully automated fashion; if available, it uses extrinsic evidence for model refinement.  ...  The pipeline has since been extended to the integration of data on mapped cross-species proteins, and to the usage of heterogeneous extrinsic evidence, both RNA-Seq and protein alignments.  ...  Acknowledgement This work is supported in part by the US National Institutes of Health grant HG000783 to MB and by German Research Foundation grant 1009/12-1 to MS. References  ... 
doi:10.1007/978-1-4939-9173-0_5 pmid:31020555 pmcid:PMC6635606 fatcat:6opvtf2u65gedouevqpiem6nuu

Bioinformatic analysis of subfamily-specific regions in 3D-structures of homologs to study functional diversity and conformational plasticity in protein superfamilies

Daria Timonina, Yana Sharapova, Vytas Švedas, Dmitry Suplatov
2021 Computational and Structural Biotechnology Journal  
We have developed Zebra3D - the first-of-its-kind bioinformatic software for systematic analysis of 3D-alignments of protein families using machine learning.  ...  at the level of amino acid sequences.  ...  Acknowledgements This work was supported by Russian Foundation for Basic Research according to the research project [18-29-13060].  ... 
doi:10.1016/j.csbj.2021.02.005 pmid:33738079 pmcid:PMC7933735 fatcat:wrgsazud3jhivghmwlnarnt3bi

Learning parameter sets for alignment advising

Dan DeBlasio, John Kececioglu
2014 Proceedings of the 5th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics - BCB '14  
The problem of picking a good choice of parameter values for specific input sequences is called parameter advising.  ...  While the multiple sequence alignment output by an aligner strongly depends on the parameter values used for the alignment scoring function (such as the choice of gap penalties and substitution scores)  ...  This work introduced new feature functions for protein multiple sequence alignments that make use of predicted secondary structure, including a feature called Secondary Structure Blockiness, whose evaluation  ... 
doi:10.1145/2649387.2649448 dblp:conf/bcb/DeBlasioK14 fatcat:m6bb6lidkbe25ooeytlwt7eixa

The Dundee Resource for Sequence Analysis and Structure Prediction

Stuart A. MacGowan, Fábio Madeira, Thiago Britto‐Borges, Mateusz Warowny, Alexey Drozdetskiy, James B. Procter, Geoffrey J. Barton
2019 Protein Science  
DRSASP's flagship services are the JPred4 webserver for secondary structure and solvent accessibility prediction and the JABAWS 2.2 webserver for multiple sequence alignment, disorder prediction, amino  ...  The Dundee Resource for Sequence Analysis and Structure Prediction (DRSASP; is a collection of web services provided by the Barton Group at the University of  ...  ACKNOWLEDGMENTS We are grateful to all authors of methods that have been included in DRSASP.  ... 
doi:10.1002/pro.3783 pmid:31710725 pmcid:PMC6933851 fatcat:ojsn3m264fhfng7zn5aupfhb5a

State-of-the-art bioinformatics protein structure prediction tools (Review)

Ioannis Michalopoulos
2011 International Journal of Molecular Medicine  
The aim of this paper is to provide the experimental biologists with a set of cutting-edge, carefully evaluated, user-friendly computational tools for protein structure prediction that would be helpful  ...  To deal with the overwhelming data, a collection of automated methods as bioinformatics tools which determine the structure of a protein from its amino acid sequence have emerged.  ...  The latter searches for the tree that best fits the information present in each column of the multiple sequence alignment.  ... 
doi:10.3892/ijmm.2011.705 pmid:21617841 fatcat:46fihfegljgwzccoeerdt2uh64
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