AIMC Topic: Datasets as Topic

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A Self-Adaptive Fuzzy -Means Algorithm for Determining the Optimal Number of Clusters.

Computational intelligence and neuroscience Nov 29, 2016
For the shortcoming of fuzzy -means algorithm (FCM) needing to know the number of clusters in advance, this paper proposed a new self-adaptive method to determine the optimal number of clusters. Firstly, a density-based algorithm was put forward. The...
Pattern Recognition, Automated Fuzzy Logic Cluster Analysis Datasets as Topic Humans Algorithms
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Prediction of Protein-Protein Interactions by Evidence Combining Methods.

International journal of molecular sciences Nov 22, 2016
Most cellular functions involve proteins' features based on their physical interactions with other partner proteins. Sketching a map of protein-protein interactions (PPIs) is therefore an important inception step towards understanding the basics of c...
High-Throughput Nucleotide Sequencing Datasets as Topic Saccharomyces cerevisiae Proteins Models, Molecular Computer Simulation Data Mining Animals Protein Interaction Mapping Drosophila melanogaster Mice Protein Interaction Domains and Motifs Molecular Sequence Annotation Computational Biology Arabidopsis Gene Ontology Support Vector Machine Humans Escherichia coli
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A new hyperbox selection rule and a pruning strategy for the enhanced fuzzy min-max neural network.

Neural networks : the official journal of the International Neural Network Society Nov 3, 2016
In this paper, we extend our previous work on the Enhanced Fuzzy Min-Max (EFMM) neural network by introducing a new hyperbox selection rule and a pruning strategy to reduce network complexity and improve classification performance. Specifically, a ne...
Fuzzy Logic Neural Networks, Computer Datasets as Topic
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Integrating network, sequence and functional features using machine learning approaches towards identification of novel Alzheimer genes.

BMC genomics Oct 18, 2016
BACKGROUND: Alzheimer's disease (AD) is a complex progressive neurodegenerative disorder commonly characterized by short term memory loss. Presently no effective therapeutic treatments exist that can completely cure this disease. The cause of Alzheim...
Machine Learning Reproducibility of Results Gene Expression Profiling Humans Alzheimer Disease Datasets as Topic Molecular Sequence Annotation Genetic Predisposition to Disease Genetic Association Studies Computational Biology Gene Ontology Protein Interaction Mapping
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TMSEG: Novel prediction of transmembrane helices.

Proteins Sep 16, 2016
Transmembrane proteins (TMPs) are important drug targets because they are essential for signaling, regulation, and transport. Despite important breakthroughs, experimental structure determination remains challenging for TMPs. Various methods have bri...
Datasets as Topic Protein Conformation, alpha-Helical Humans Machine Learning Sensitivity and Specificity Membrane Proteins Databases, Protein Hydrophobic and Hydrophilic Interactions
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Effect of Protein Repetitiveness on Protein-Protein Interaction Prediction Results Using Support Vector Machines.

Journal of computational biology : a journal of computational molecular cell biology Aug 16, 2016
BACKGROUND: There are many computational approaches to predict the protein-protein interactions using support vector machines (SVMs) with high performance. In fact, performance of currently reported methods are significantly over-estimated and affect...
Datasets as Topic Saccharomyces cerevisiae Protein Interaction Mapping Support Vector Machine Humans Proteins
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Predicting the Presence of Uncommon Elements in Unknown Biomolecules from Isotope Patterns.

Analytical chemistry Jul 22, 2016
The determination of the molecular formula is one of the earliest and most important steps when investigating the chemical nature of an unknown compound. Common approaches use the isotopic pattern of a compound measured using mass spectrometry. Compu...
Isotopes Machine Learning Molecular Weight Algorithms Datasets as Topic Chemical Phenomena Mass Spectrometry Elements
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Longitudinal clinical score prediction in Alzheimer's disease with soft-split sparse regression based random forest.

Neurobiology of aging Jul 15, 2016
Alzheimer's disease (AD) is an irreversible neurodegenerative disease and affects a large population in the world. Cognitive scores at multiple time points can be reliably used to evaluate the progression of the disease clinically. In recent studies,...
Linear Models Neuroimaging Diffusion Magnetic Resonance Imaging Predictive Value of Tests Humans Alzheimer Disease Machine Learning Datasets as Topic Brain Longitudinal Studies Male Regression Analysis Female Disease Progression Aged Severity of Illness Index Aged, 80 and over
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Machine learning, statistical learning and the future of biological research in psychiatry.

Psychological medicine Jul 13, 2016
Psychiatric research has entered the age of 'Big Data'. Datasets now routinely involve thousands of heterogeneous variables, including clinical, neuroimaging, genomic, proteomic, transcriptomic and other 'omic' measures. The analysis of these dataset...
Humans Machine Learning Psychiatry Biomedical Research Datasets as Topic Probability Learning
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An Ensemble Approach for Cognitive Fault Detection and Isolation in Sensor Networks.

International journal of neural systems Jun 26, 2016
Cognitive fault detection and diagnosis systems are systems able to provide timely information about possibly occurring faults without requiring any a priori knowledge about the process generating the data or the possible faults. This ability is cruc...
Markov Chains Datasets as Topic Landslides Neural Networks, Computer Computer Simulation Algorithms Cognition Italy
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