AIMC Topic: Support Vector Machine

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Highly predictive support vector machine (SVM) models for anthrax toxin lethal factor (LF) inhibitors.

Journal of molecular graphics & modelling Nov 17, 2015
Anthrax is a highly lethal, acute infectious disease caused by the rod-shaped, Gram-positive bacterium Bacillus anthracis. The anthrax toxin lethal factor (LF), a zinc metalloprotease secreted by the bacilli, plays a key role in anthrax pathogenesis ...
Support Vector Machine Models, Statistical Predictive Value of Tests High-Throughput Screening Assays Databases, Chemical Structure-Activity Relationship Models, Chemical User-Computer Interface Bacterial Toxins Antidotes Antigens, Bacterial Bacillus anthracis Small Molecule Libraries
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The feature selection bias problem in relation to high-dimensional gene data.

Artificial intelligence in medicine Nov 14, 2015
OBJECTIVE: Feature selection is a technique widely used in data mining. The aim is to select the best subset of features relevant to the problem being considered. In this paper, we consider feature selection for the classification of gene datasets. G...
Pattern Recognition, Automated Humans Oligonucleotide Array Sequence Analysis Algorithms Bias Computational Biology Decision Support Techniques Data Mining Gene Expression Regulation, Neoplastic Linear Models Support Vector Machine Reproducibility of Results Databases, Genetic Biomarkers, Tumor Gene Expression Profiling
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Diagnosis of Brain Metastases from Lung Cancer Using a Modified Electromagnetism like Mechanism Algorithm.

Journal of medical systems Nov 14, 2015
Brain metastases are commonly found in patients that are diagnosed with primary malignancy on their lung. Lung cancer patients with brain metastasis tend to have a poor survivability, which is less than 6 months in median. Therefore, an early and eff...
Female Aged Brain Neoplasms Humans Algorithms Support Vector Machine Taiwan Male Middle Aged Lung Neoplasms
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Classification of radiology reports for falls in an HIV study cohort.

Journal of the American Medical Informatics Association : JAMIA Nov 13, 2015
OBJECTIVE: To identify patients in a human immunodeficiency virus (HIV) study cohort who have fallen by applying supervised machine learning methods to radiology reports of the cohort.
Area Under Curve Unified Medical Language System Radiology Information Systems United States Department of Veterans Affairs Cohort Studies Accidental Falls United States Support Vector Machine HIV Infections Humans Electronic Health Records Veterans
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Predict Gram-Positive and Gram-Negative Subcellular Localization via Incorporating Evolutionary Information and Physicochemical Features Into Chou's General PseAAC.

IEEE transactions on nanobioscience Nov 12, 2015
In this study, we used structural and evolutionary based features to represent the sequences of gram-positive and gram-negative subcellular localizations. To do this, we proposed a normalization method to construct a normalize Position Specific Scori...
Bayes Theorem Gram-Negative Bacteria Gram-Positive Bacteria Support Vector Machine Intracellular Space Models, Statistical
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Prediction the Substrate Specificities of Membrane Transport Proteins Based on Support Vector Machine and Hybrid Features.

IEEE/ACM transactions on computational biology and bioinformatics Nov 11, 2015
Membrane transport proteins and their substrate specificities play crucial roles in a variety of cellular functions. Identifying the substrate specificities of membrane transport proteins is closely related to the protein-target interaction predictio...
Algorithms Molecular Docking Simulation Pattern Recognition, Automated Substrate Specificity Membrane Transport Proteins Protein Interaction Mapping Binding Sites Sequence Analysis, Protein Protein Binding Support Vector Machine Models, Chemical
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Machine Learning Approaches for Predicting Radiation Therapy Outcomes: A Clinician's Perspective.

International journal of radiation oncology, biology, physics Nov 11, 2015
Radiation oncology has always been deeply rooted in modeling, from the early days of isoeffect curves to the contemporary Quantitative Analysis of Normal Tissue Effects in the Clinic (QUANTEC) initiative. In recent years, medical modeling for both pr...
Xerostomia Support Vector Machine Models, Statistical Radiation Oncology Esophagitis Radiation Pneumonitis Radiotherapy Dosage Neural Networks, Computer Radiotherapy Lung Neoplasms Artificial Intelligence Machine Learning Logistic Models Humans Prognosis Treatment Outcome Reproducibility of Results
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An adaptive classification model for peptide identification.

BMC genomics Nov 10, 2015
BACKGROUND: Peptide sequence assignment is the central task in protein identification with MS/MS-based strategies. Although a number of post-database search algorithms for filtering target peptide spectrum matches (PSMs) have been developed, the disc...
Computational Biology Humans Support Vector Machine Algorithms Peptides
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Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics.

PloS one Nov 10, 2015
We introduce a new representation and feature extraction method for biological sequences. Named bio-vectors (BioVec) to refer to biological sequences in general with protein-vectors (ProtVec) for proteins (amino-acid sequences) and gene-vectors (Gene...
Intrinsically Disordered Proteins Protein Structure, Secondary Computational Biology Nuclear Pore Complex Proteins Genomics Proteomics Proteins Databases, Protein Support Vector Machine Natural Language Processing Amino Acid Sequence
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Gene and sample selection using T-score with sample selection.

Journal of biomedical informatics Nov 7, 2015
Gene selection from high-dimensional microarray gene-expression data is statistically a challenging problem. Filter approaches to gene selection have been popular because of their simplicity, efficiency, and accuracy. Due to small sample size, all sa...
Computational Biology Logistic Models Support Vector Machine Databases, Genetic Algorithms Gene Expression Profiling
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