Special Protein Molecules Computational Identification
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Quan Zou | Wenying He | Q. Zou | Wenying He
[1] Long Zhang,et al. Protein-Protein Interactions Prediction Using a Novel Local Conjoint Triad Descriptor of Amino Acid Sequences , 2017, International journal of molecular sciences.
[2] Lei Chen,et al. Application of the Shortest Path Algorithm for the Discovery of Breast Cancer-Related Genes , 2016 .
[3] Pufeng Du,et al. PseAAC-General: Fast Building Various Modes of General Form of Chou’s Pseudo-Amino Acid Composition for Large-Scale Protein Datasets , 2014, International journal of molecular sciences.
[4] Xiangxiang Zeng,et al. nDNA-prot: identification of DNA-binding proteins based on unbalanced classification , 2014, BMC Bioinformatics.
[5] Bo Chen,et al. Biochemical and Computational Insights on a Novel Acid-Resistant and Thermal-Stable Glucose 1-Dehydrogenase , 2017, International journal of molecular sciences.
[6] B. Snel,et al. Predicting disease genes using protein–protein interactions , 2006, Journal of Medical Genetics.
[7] Bo Li,et al. Protein Complexes Prediction Method Based on Core—Attachment Structure and Functional Annotations , 2017, International journal of molecular sciences.
[8] Kamila Korzekwa,et al. Relationship of Triamine-Biocide Tolerance of Salmonella enterica Serovar Senftenberg to Antimicrobial Susceptibility, Serum Resistance and Outer Membrane Proteins , 2017, International journal of molecular sciences.
[9] Jijun Tang,et al. Identification of drug-target interactions via multiple information integration , 2017, Inf. Sci..
[10] Jianxin Wang,et al. CytoCluster: A Cytoscape Plugin for Cluster Analysis and Visualization of Biological Networks , 2017, International journal of molecular sciences.
[11] Yi Pan,et al. ClusterViz: A Cytoscape APP for Cluster Analysis of Biological Network , 2015, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[12] Hui Ding,et al. Predicting ion channels and their types by the dipeptide mode of pseudo amino acid composition. , 2011, Journal of theoretical biology.
[13] Dong Xu,et al. Transmembrane Protein Alignment and Fold Recognition Based on Predicted Topology , 2013, PloS one.
[14] Shunfang Wang,et al. Protein Sub-Nuclear Localization Based on Effective Fusion Representations and Dimension Reduction Algorithm LDA , 2015, International journal of molecular sciences.
[15] Jian Song,et al. Identification of DNA–protein Binding Sites through Multi-Scale Local Average Blocks on Sequence Information , 2017, Molecules.
[16] B. Liu,et al. DNA binding protein identification by combining pseudo amino acid composition and profile-based protein representation , 2015, Scientific Reports.
[17] B. Liu,et al. PSFM-DBT: Identifying DNA-Binding Proteins by Combing Position Specific Frequency Matrix and Distance-Bigram Transformation , 2017, International journal of molecular sciences.
[18] Xing Chen,et al. PCVMZM: Using the Probabilistic Classification Vector Machines Model Combined with a Zernike Moments Descriptor to Predict Protein–Protein Interactions from Protein Sequences , 2017, International journal of molecular sciences.
[19] Jijun Tang,et al. PhosPred-RF: A Novel Sequence-Based Predictor for Phosphorylation Sites Using Sequential Information Only , 2017, IEEE Transactions on NanoBioscience.
[20] Jian Gao,et al. Identification of Direct Activator of Adenosine Monophosphate-Activated Protein Kinase (AMPK) by Structure-Based Virtual Screening and Molecular Docking Approach , 2017, International journal of molecular sciences.
[21] Xuan Liu,et al. Identification of DNA-Binding Proteins by Combining Auto-Cross Covariance Transformation and Ensemble Learning , 2016, IEEE Transactions on NanoBioscience.
[22] Xinying Xu,et al. An Ameliorated Prediction of Drug–Target Interactions Based on Multi-Scale Discrete Wavelet Transform and Network Features , 2017, International journal of molecular sciences.
[23] Hua Tang,et al. IonchanPred 2.0: A Tool to Predict Ion Channels and Their Types , 2017, International journal of molecular sciences.
[24] Jinyan Li,et al. Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information , 2010, BMC Bioinformatics.
[25] Jingpu Zhang,et al. Integrating Multiple Heterogeneous Networks for Novel LncRNA-Disease Association Inference , 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[26] Bo Liu,et al. A Topology Structure Based Outer Membrane Proteins Segment Alignment Method , 2013 .
[27] Junjie Chen,et al. Pse-in-One: a web server for generating various modes of pseudo components of DNA, RNA, and protein sequences , 2015, Nucleic Acids Res..
[28] B. Liu,et al. PseDNA‐Pro: DNA‐Binding Protein Identification by Combining Chou’s PseAAC and Physicochemical Distance Transformation , 2015, Molecular informatics.
[29] Jinyan Li,et al. Protein binding hot spots prediction from sequence only by a new ensemble learning method , 2017, Amino Acids.
[30] Wei Chen,et al. Detecting N6-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines , 2017, Scientific Reports.
[31] Wei Ding,et al. 3D-QSAR and Molecular Docking Studies on the TcPMCA1-Mediated Detoxification of Scopoletin and Coumarin Derivatives , 2017, International journal of molecular sciences.
[32] Wei Zhao,et al. UltraPse: A Universal and Extensible Software Platform for Representing Biological Sequences , 2017, International journal of molecular sciences.
[33] B. Liu,et al. iDNA-Prot|dis: Identifying DNA-Binding Proteins by Incorporating Amino Acid Distance-Pairs and Reduced Alphabet Profile into the General Pseudo Amino Acid Composition , 2014, PloS one.
[34] Shunfang Wang,et al. Protein Subcellular Localization with Gaussian Kernel Discriminant Analysis and Its Kernel Parameter Selection , 2017, International journal of molecular sciences.
[35] Xiangrong Liu,et al. An Empirical Study of Features Fusion Techniques for Protein-Protein Interaction Prediction , 2016 .
[36] Tingting Fu,et al. Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics , 2017, Nucleic Acids Res..
[37] Pu-Feng Du,et al. Predicting Golgi-resident protein types using pseudo amino acid compositions: Approaches with positional specific physicochemical properties. , 2016, Journal of theoretical biology.
[38] Yuhang Zhang,et al. Determination of Genes Related to Uveitis by Utilization of the Random Walk with Restart Algorithm on a Protein–Protein Interaction Network , 2017, International journal of molecular sciences.
[39] Jinyan Li,et al. Accurate prediction of hot spot residues through physicochemical characteristics of amino acid sequences , 2013, Proteins.
[40] Yi Pan,et al. Identification of Protein Complexes by Using a Spatial and Temporal Active Protein Interaction Network , 2020, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[41] Jinyan Li,et al. A Sequence-Based Dynamic Ensemble Learning System for Protein Ligand-Binding Site Prediction , 2016, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[42] Bo Li,et al. NOREVA: normalization and evaluation of MS-based metabolomics data , 2017, Nucleic Acids Res..
[43] Yi Pan,et al. DyNetViewer: a Cytoscape app for dynamic network construction, analysis and visualization , 2018, Bioinform..
[44] Jijun Tang,et al. Predicting protein-protein interactions via multivariate mutual information of protein sequences , 2016, BMC Bioinformatics.
[45] Guohua Wang,et al. Identification of DNA-Binding Proteins Using Mixed Feature Representation Methods , 2017, Molecules.
[46] Feng Zhu,et al. Assessing the Performances of Protein Function Prediction Algorithms from the Perspectives of Identification Accuracy and False Discovery Rate , 2018, International journal of molecular sciences.
[47] Lei Chen,et al. An integrated method for the identification of novel genes related to oral cancer , 2017, PloS one.
[48] Xin Wang,et al. PseAAC-Builder: a cross-platform stand-alone program for generating various special Chou's pseudo-amino acid compositions. , 2012, Analytical biochemistry.
[49] Jijun Tang,et al. Identification of Protein–Protein Interactions via a Novel Matrix-Based Sequence Representation Model with Amino Acid Contact Information , 2016, International journal of molecular sciences.
[50] Zixiang Wang,et al. Computational identification of binding energy hot spots in protein–RNA complexes using an ensemble approach , 2018, Bioinform..
[51] Bin Liu,et al. BioSeq-Analysis: a platform for DNA, RNA and protein sequence analysis based on machine learning approaches , 2019, Briefings Bioinform..
[52] Jian Zhang,et al. Identification of novel proliferative diabetic retinopathy related genes on protein-protein interaction network , 2016, Neurocomputing.
[53] Q. Zou,et al. Network-based method for mining novel HPV infection related genes using random walk with restart algorithm. , 2017, Biochimica et biophysica acta. Molecular basis of disease.
[54] Lin Wu,et al. CytoCtrlAnalyser: a Cytoscape app for biomolecular network controllability analysis , 2018, Bioinform..
[55] Jijun Tang,et al. Local-DPP: An improved DNA-binding protein prediction method by exploring local evolutionary information , 2017, Inf. Sci..
[56] Ricardo L. Mancera,et al. Understanding Insulin Endocrinology in Decapod Crustacea: Molecular Modelling Characterization of an Insulin-Binding Protein and Insulin-Like Peptides in the Eastern Spiny Lobster, Sagmariasus verreauxi , 2017, International journal of molecular sciences.
[57] Yi Pan,et al. CytoNCA: A cytoscape plugin for centrality analysis and evaluation of protein interaction networks , 2015, Biosyst..
[58] Bing Wang,et al. Prediction of Protein Hotspots from Whole Protein Sequences by a Random Projection Ensemble System , 2017, International journal of molecular sciences.
[59] Dong Xu,et al. OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method , 2017, J. Comput. Biol..
[60] Anton A Nizhnikov,et al. Predicting Amyloidogenic Proteins in the Proteomes of Plants , 2017, International journal of molecular sciences.
[61] Shuang Li,et al. SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity , 2016, PloS one.
[62] Wei Chen,et al. Identifying the Subfamilies of Voltage-Gated Potassium Channels Using Feature Selection Technique , 2014, International journal of molecular sciences.
[63] Wei Chen,et al. Identification of voltage-gated potassium channel subfamilies from sequence information using support vector machine , 2012, Comput. Biol. Medicine.
[64] Shunfang Wang,et al. A New Feature Extraction Method Based on the Information Fusion of Entropy Matrix and Covariance Matrix and Its Application in Face Recognition , 2015, Entropy.
[65] Lei Deng,et al. A computational interactome and functional annotation for the human proteome , 2016, eLife.