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An improved sequence based prediction protocol for DNA-binding proteins using SVM and comprehensive feature analysis
2013
BMC Bioinformatics
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Conclusions: The good results suggest that it can efficiently develop an entirely sequence-based protocol that transforms and integrates informative features from different scales used by SVM to predict ...
Results: In this work, the focus is how to transform these informative features into uniform numeric representation appropriately and improve the prediction accuracy of our SVM-based classifier for DNA-BPs ...
We propose a novel method for predicting DNA-BPs using the SVM algorithm in conjunction with comprehensive feature analysis based on protein sequence. ...
doi:10.1186/1471-2105-14-90
pmid:23497329
pmcid:PMC3602657
fatcat:6spnbrgrnrc2vccm4evjie3pbm
Identifying DNA-binding proteins by combining support vector machine and PSSM distance transformation
2015
BMC Systems Biology
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Conclusions:: The experiment results demonstrate that PSSM Distance Transformation is an available protein sequence encoding method and SVM-PSSM-DT is a useful tool for identifying the DNA-binding proteins ...
However, most of them can't provide an invaluable knowledge base for our understanding of DNA-protein interactions. ...
For example, use the protein 1IGN chain B as a query sequence, you will see on your screen that the predictive result is "DNA-binding protein". ...
doi:10.1186/1752-0509-9-s1-s10
pmid:25708928
pmcid:PMC4331676
fatcat:x6dvikx52ndtloc563osetzgtm
Residue-level prediction of DNA-binding sites and its application on DNA-binding protein predictions
2007
FEBS Letters
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In this study, we have three aims focusing on DNA-binding residues on the protein surface: to develop an automated approach for fast and reliable recognition of DNA-binding sites; to improve the prediction ...
We use a support vector machines (SVM)based approach to harness the features of the DNA-binding residues to distinguish them from non-binding residues. ...
A few computational protocols have been developed for automated identification of DNA-binding residues based on the features derived from sequence and structure collectively and those from sequence alone ...
doi:10.1016/j.febslet.2007.01.086
pmid:17316627
pmcid:PMC1993824
fatcat:vn2t24mulrepfifzkf6g3dfdqu
Prediction of DNA-binding residues from sequence
2007
Computer applications in the biosciences : CABIOS
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Motivation: Thousands of proteins are known to bind to DNA; for most of them the mechanism of action and the residues that bind to DNA, i.e. the binding sites, are yet unknown. ...
If the 3D structure of a protein is known, it is often possible to predict DNA-binding sites in silico. However, for most proteins, such knowledge is not available. ...
We thank Jinfeng Liu, Andrew Kernytsky and Michael Honig (Columbia University) for help with computers and databases. ...
doi:10.1093/bioinformatics/btm174
pmid:17646316
fatcat:ehc3xdoiq5gjtfpg2lm77nb6qq
DNABind: A hybrid algorithm for structure-based prediction of DNA-binding residues by combining machine learning- and template-based approaches
2013
Proteins: Structure, Function, and Bioinformatics
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Xiong et al. 9 integrated SVM with four features including sequence profile, solvent accessibility, packing density, and pK a value to recognize DNA-binding residues. ...
to conduct structural and functional analysis on the interfaces between proteins and DNA with computational methods. ...
of each residue in a protein sequence. 12
Machine learning-based prediction protocol Here a machine learning-based algorithm was proposed for the prediction of DNA-binding residues, where the Support ...
doi:10.1002/prot.24330
pmid:23737141
fatcat:znqcqtyoz5f6flhqhnr5h6fvhq
Bridging protein local structures and protein functions
2008
Amino Acids
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of sequence and structure data. ...
One of the major goals of molecular and evolutionary biology is to understand the functions of proteins by extracting functional information from protein sequences, structures and interactions. ...
The authors are grateful to the anonymous referees as well as editors for comments and for helping to improve the earlier version. ...
doi:10.1007/s00726-008-0088-8
pmid:18421562
fatcat:micrifjcrfetnafnm4fx45ouom
DNABP: Identification of DNA-Binding Proteins Based on Feature Selection Using a Random Forest and Predicting Binding Residues
2016
PLoS ONE
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DNA-binding proteins are fundamentally important in cellular processes. Several computational-based methods have been developed to improve the prediction of DNA-binding proteins in previous years. ...
In this paper, a novel predictor, DNABP (DNA-binding proteins), was designed to predict DNA-binding proteins using the random forest (RF) classifier with a hybrid feature. ...
The authors would also like to thank the two anonymous reviewers for their constructive comments, which were very helpful for strengthening the presentation of this study. ...
doi:10.1371/journal.pone.0167345
pmid:27907159
pmcid:PMC5132331
fatcat:3oahir4dgvcz3bwvkvlyurwlnu
Integrating sequence and gene expression information predicts genome-wide DNA-binding proteins and suggests a cooperative mechanism
2017
Nucleic Acids Research
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While our sequence-based models outperformed the gene expression-based ones, some proteins with weaker DBP-like sequence features were correctly predicted by gene expression-based features, suggesting ...
To address these issues, we have developed novel methods for predicting DBPs by integrating sequence and gene expression-derived features and applied them to explore human, mouse and Arabidopsis proteomes ...
., contributed through critical discussions and helped in improving the manuscript. ...
doi:10.1093/nar/gkx1166
pmid:29186632
pmcid:PMC5758906
fatcat:uudle3my7rg7hneb34lmq6s4be
Predicting transcription factor site occupancy using DNA sequence intrinsic and cell-type specific chromatin features
2016
BMC Bioinformatics
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DNA sequence intrinsic features such as predicted binding affinity are often not very effective in predicting in vivo site occupancy and in any case could not explain cell-type specific binding events. ...
In this work, we use machine-learning methods to build predictive models and assess the relative importance of different sequence-intrinsic and chromatin features in the TF-to-target-site recruitment process ...
Declarations Publication charges for this article have been funded by the Swiss Federal Institute of Technology Lausanne (EPFL). ...
doi:10.1186/s12859-015-0846-z
pmid:26818008
pmcid:PMC4895346
fatcat:wgalgvjcgbharggldcj34remga
DHSpred: support-vector-machine-based human DNase I hypersensitive sites prediction using the optimal features selected by random forest
2017
OncoTarget
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In this study, we proposed a support vector machine (SVM)-based method for predicting DHSs, called DHSpred (DNase I Hypersensitive Site predictor in human DNA sequences), which was trained with 174 optimal ...
Therefore, identifying DHSs in uncharacterized DNA sequences is crucial for understanding their biological functions and mechanisms. ...
The copyright holder for this preprint (which was . ...
doi:10.18632/oncotarget.23099
pmid:29416743
pmcid:PMC5788611
fatcat:3eadyivd2fgltpynb7ohpxn2eu
Sequence-Based Prediction of RNA-Binding Residues in Proteins
[chapter]
2016
Msphere
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Step-by-step protocols for using three different web-based servers to predict RNA-binding residues are described. ...
We emphasize sequence-based methods that can reliably identify interfacial residues without the requirement for structural information regarding either the RNA-binding protein or its RNA partner. 206 16 ...
RRW is currently supported by an appointment to the ARS-USDA Research Participation Program administered by the Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between ...
doi:10.1007/978-1-4939-6406-2_15
pmid:27787829
pmcid:PMC5796408
fatcat:552w4ny4rvcntj3kv55phjpfii
Sequence-Based Prediction of RNA-Binding Proteins Using Random Forest with Minimum Redundancy Maximum Relevance Feature Selection
2015
BioMed Research International
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High prediction accuracy and successful prediction performance suggested that our method can be a useful approach to identify RNA-binding proteins from sequence information. ...
In this study, a highly accurate method was developed to predict RNA-binding proteins from amino acid sequences using random forests with the minimum redundancy maximum relevance (mRMR) method, followed ...
proposed an SVM-based predictor using a conjoint triad feature, which extracts information directly from the amino acids sequences of proteins [10] . ...
doi:10.1155/2015/425810
pmid:26543860
pmcid:PMC4620426
fatcat:jcp5vobu7jb77ista7dazoqtpi
Prediction of RNA- and DNA-Binding Proteins Using Various Machine Learning Classifiers
2019
Avicenna journal of medical biotechnology
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In the current study, nine machine-learning algorithms were used to predict RNA- and DNA-binding proteins and also to discriminate between RNA-binding proteins and DNA-binding proteins. ...
Our findings show that the prediction of nucleic acid-binding function based on these simple electrostatic features can be improved by applied classifiers. ...
Acknowledgement We would like to thank Dr Ebrahim Barzegari Asadabadi for his useful comments. ...
pmid:30800250
pmcid:PMC6359699
fatcat:eaq32ciwabbpniw2czndsm4ghu
Computational challenges in modeling gene regulatory events
2016
Transcription
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This article gives an exemplified account of the current computational challenges in molecular biology. ...
Cellular transcriptional programs driven by genetic and epigenetic mechanisms could be better understood by integrating "omics" data and subsequently modeling the gene-regulatory events. ...
For the flanking regions of these motifs, information is extracted from DNA structure (DNAshape), sequence features, and chromatin state dynamics to build the classifying model (i.e., SVM, RBF, or Regression ...
doi:10.1080/21541264.2016.1204491
pmid:27390891
pmcid:PMC5066510
fatcat:x6eatpawrvg2dnr4dhivj4yqty
A novel artificial intelligence-based approach for identification of deoxynucleotide aptamers
2021
PLoS Computational Biology
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of DNA-binding sequences. ...
Usually, 10 to 20 steps are required for SELEX to be completed. Throughout this process it is necessary to discriminate between true DNA aptamers and unspecified DNA-binding sequences. ...
Vázquez-Quiñones, professor of the School of Sciences and Technology of the Universidad Metropolitana-Ana G. Méndez, for his comments and suggestions during the writing of this manuscript. ...
doi:10.1371/journal.pcbi.1009247
pmid:34343165
pmcid:PMC8362955
fatcat:cmnednyusvcxjivnxsg5ar5gmy
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