Pattern Recognition in Bioinformatics
Springer International Publishing (Verlag)
978-3-319-09191-4 (ISBN)
FULL PAPERS.- Acquiring Decision Rules for Predicting Ames-Negative Hepatocarcinogens Using Chemical-Chemical Interactions.- Using Topology Information for Protein-Protein Interaction Prediction.- Biases of drug{target interaction network data.- Logol: Expressive Pattern Matching in sequences Application to Ribosomal Frameshift Modeling.- Evolutionary Algorithm based on New Crossover for the Biclustering of Gene Expression Data.- SFFS-SW: A feature selection algorithm exploring the small-world properties of GNs.- CytomicsDB: A Metadata-based storage and retrieval approach for High-Throughput Screening Experiments.- CUDAGRN: Parallel Speedup of Inferring Large Gene Regulatory.- Networks from Expression Data Using Random Forest.- SHORT ABSTRACTS.- Analysis of miRNA expression profiles in breast cancer using biclustering.- Gram-positive and Gram-negative Subcellular Localization Using Rotation Forest and Physicochemical-based Features.- Data Driven Feature Selection for RNA-Seq Differential Expression Analysis.- Intramuscular fat percentage estimation through ultrasound images.- An integrated approach of gene expression and DNA-methylation profiles of WNT signaling genes uncovers novel prognostic markers in Acute Myeloid Leukemia.- Improving performance of the eXtasy model by hierarchical sampling.- Popovic et al.Ensemble Neural Networks Scoring Functions for Accurate Binding Affinity.- Prediction of Protein-Ligand Complexes.- Integration of Gene Expression and DNA-methylation Profiles Improves Molecular Subtype Classification in Acute Myeloid Leukemia.- The Relative Vertex-to-Vertex Clustering Value- A New Criterion for the Fast Detection of Functional Modules in Protein Interaction Networks.
Erscheint lt. Verlag | 5.8.2014 |
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Reihe/Serie | Lecture Notes in Bioinformatics | Lecture Notes in Computer Science |
Zusatzinfo | XII, 135 p. 29 illus. |
Verlagsort | Cham |
Sprache | englisch |
Maße | 155 x 235 mm |
Gewicht | 237 g |
Themenwelt | Informatik ► Weitere Themen ► Bioinformatik |
Naturwissenschaften ► Biologie | |
Schlagworte | Algorithm analysis and problem complexity • Bioinformatics • classification • Computational Biology • computational proteomics • Data Mining • graph theory • Information Theory • Pattern Matching • pattern recognition • Protein-Protein Interaction Prediction • Support Vector Machines |
ISBN-10 | 3-319-09191-3 / 3319091913 |
ISBN-13 | 978-3-319-09191-4 / 9783319091914 |
Zustand | Neuware |
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