AIMC Topic: DNA-Binding Proteins

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SDBP-Pred: Prediction of single-stranded and double-stranded DNA-binding proteins by extending consensus sequence and K-segmentation strategies into PSSM.

Analytical biochemistry Nov 3, 2019
Identification of DNA-binding proteins (DNA-BPs) is a hot issue in protein science due to its key role in various biological processes. These processes are highly concerned with DNA-binding protein types. DNA-BPs are classified into single-stranded D...
Computational Biology Amino Acid Sequence Datasets as Topic Consensus Sequence Support Vector Machine Databases, Protein DNA-Binding Proteins
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FKRR-MVSF: A Fuzzy Kernel Ridge Regression Model for Identifying DNA-Binding Proteins by Multi-View Sequence Features via Chou's Five-Step Rule.

International journal of molecular sciences Aug 26, 2019
DNA-binding proteins play an important role in cell metabolism. In biological laboratories, the detection methods of DNA-binding proteins includes yeast one-hybrid methods, bacterial singles and X-ray crystallography methods and others, but these met...
Regression Analysis DNA-Binding Proteins Sensitivity and Specificity ROC Curve Computational Biology Machine Learning Reproducibility of Results
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Enabling full-length evolutionary profiles based deep convolutional neural network for predicting DNA-binding proteins from sequence.

Proteins Jul 8, 2019
Sequence based DNA-binding protein (DBP) prediction is a widely studied biological problem. Sliding windows on position specific substitution matrices (PSSMs) rows predict DNA-binding residues well on known DBPs but the same models cannot be applied ...
Humans Neural Networks, Computer Protein Conformation Binding Sites Arabidopsis Proteins Arabidopsis Amino Acids Animals DNA-Binding Proteins Mice Models, Biological DNA
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Modeling in-vivo protein-DNA binding by combining multiple-instance learning with a hybrid deep neural network.

Scientific reports Jun 11, 2019
Modeling in-vivo protein-DNA binding is not only fundamental for further understanding of the regulatory mechanisms, but also a challenging task in computational biology. Deep-learning based methods have succeed in modeling in-vivo protein-DNA bindin...
Neural Networks, Computer Algorithms Deep Learning Humans Models, Biological Protein Binding DNA DNA-Binding Proteins
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DP-BINDER: machine learning model for prediction of DNA-binding proteins by fusing evolutionary and physicochemical information.

Journal of computer-aided molecular design May 23, 2019
DNA-binding proteins (DBPs) participate in various biological processes including DNA replication, recombination, and repair. In the human genome, about 6-7% of these proteins are utilized for genes encoding. DBPs shape the DNA into a compact structu...
Binding Sites Position-Specific Scoring Matrices Animals Support Vector Machine Evolution, Molecular Databases, Protein DNA DNA-Binding Proteins Humans Machine Learning Algorithms
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DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines.

Journal of chemical information and modeling Apr 16, 2019
Accurate identification of protein-DNA binding sites is significant for both understanding protein function and drug design. Machine-learning-based methods have been extensively used for the prediction of protein-DNA binding sites. However, the data ...
DNA-Binding Proteins Protein Conformation Nucleic Acid Conformation Support Vector Machine DNA Models, Molecular
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TargetDBP: Accurate DNA-Binding Protein Prediction Via Sequence-Based Multi-View Feature Learning.

IEEE/ACM transactions on computational biology and bioinformatics Jan 18, 2019
Accurately identifying DNA-binding proteins (DBPs) from protein sequence information is an important but challenging task for protein function annotations. In this paper, we establish a novel computational method, named TargetDBP, for accurately targ...
Sequence Analysis, Protein Position-Specific Scoring Matrices Support Vector Machine Machine Learning Databases, Protein Algorithms DNA-Binding Proteins Computational Biology
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Radiogenomics in Clear Cell Renal Cell Carcinoma: Machine Learning-Based High-Dimensional Quantitative CT Texture Analysis in Predicting PBRM1 Mutation Status.

AJR. American journal of roentgenology Jan 2, 2019
OBJECTIVE: The purpose of this study is to evaluate the potential value of machine learning (ML)-based high-dimensional quantitative CT texture analysis in predicting the mutation status of the gene encoding the protein polybromo-1 (PBRM1) in patient...
Tomography, X-Ray Computed Female Reproducibility of Results Aged Male Middle Aged Machine Learning Algorithms Retrospective Studies Humans Predictive Value of Tests DNA-Binding Proteins Mutation Nuclear Proteins Kidney Neoplasms Transcription Factors Radiographic Image Interpretation, Computer-Assisted Carcinoma, Renal Cell Contrast Media
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PDRLGB: precise DNA-binding residue prediction using a light gradient boosting machine.

BMC bioinformatics Dec 31, 2018
BACKGROUND: Identifying specific residues for protein-DNA interactions are of considerable importance to better recognize the binding mechanism of protein-DNA complexes. Despite the fact that many computational DNA-binding residue prediction approach...
DNA-Binding Proteins Humans Protein Conformation Computational Biology Machine Learning Support Vector Machine Binding Sites Algorithms DNA Protein Binding
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Prediction of DNA-Binding Residues in Local Segments of Protein Sequences with Fuzzy Cognitive Maps.

IEEE/ACM transactions on computational biology and bioinformatics Dec 28, 2018
While protein-DNA interactions are crucial for a wide range of cellular functions, only a small fraction of these interactions was annotated to date. One solution to close this annotation gap is to employ computational methods that accurately predict...
DNA DNA-Binding Proteins Computational Biology Machine Learning Fuzzy Logic Algorithms Databases, Protein
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