AIMC Topic: Probability

Clear Filters Showing 351 to 360 of 438 articles

DisPredict: A Predictor of Disordered Protein Using Optimized RBF Kernel.

PloS one
Intrinsically disordered proteins or, regions perform important biological functions through their dynamic conformations during binding. Thus accurate identification of these disordered regions have significant implications in proper annotation of fu...

Fully automatized renal parenchyma volumetry using a support vector machine based recognition system for subject-specific probability map generation in native MR volume data.

Physics in medicine and biology
In epidemiological studies as well as in clinical practice the amount of produced medical image data strongly increased in the last decade. In this context organ segmentation in MR volume data gained increasing attention for medical applications. Esp...

iTIS-PseKNC: Identification of Translation Initiation Site in human genes using pseudo k-tuple nucleotides composition.

Computers in biology and medicine
Translation is an essential genetic process for understanding the mechanism of gene expression. Due to the large number of protein sequences generated in the post-genomic era, conventional methods are unable to identify Translation Initiation Site (T...

High-Density Liquid-State Machine Circuitry for Time-Series Forecasting.

International journal of neural systems
Spiking neural networks (SNN) are the last neural network generation that try to mimic the real behavior of biological neurons. Although most research in this area is done through software applications, it is in hardware implementations in which the ...

A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity.

PloS one
Agri-food is one of the most important sectors of the industry and a major contributor to the global warming potential in Europe. Sustainability issues pose a huge challenge for this sector. In this context, a big issue is to be able to predict the m...

Impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach.

Neural networks : the official journal of the International Neural Network Society
This paper studies the impulsive synchronization of Markovian jumping randomly coupled neural networks with partly unknown transition probabilities via multiple integral approach. The array of neural networks are coupled in a random fashion which is ...

Reconciliation of Decision-Making Heuristics Based on Decision Trees Topologies and Incomplete Fuzzy Probabilities Sets.

PloS one
Complex decision making tasks of different natures, e.g. economics, safety engineering, ecology and biology, are based on vague, sparse, partially inconsistent and subjective knowledge. Moreover, decision making economists / engineers are usually not...

A novel method based on physicochemical properties of amino acids and one class classification algorithm for disease gene identification.

Journal of biomedical informatics
Identifying the genes that cause disease is one of the most challenging issues to establish the diagnosis and treatment quickly. Several interesting methods have been introduced for disease gene identification for a decade. In general, the main diffe...

Identifying synonymy between relational phrases using word embeddings.

Journal of biomedical informatics
Many text mining applications in the biomedical domain benefit from automatic clustering of relational phrases into synonymous groups, since it alleviates the problem of spurious mismatches caused by the diversity of natural language expressions. Mos...

Identifying neuroanatomical signatures of anorexia nervosa: a multivariate machine learning approach.

Psychological medicine
BACKGROUND: There are currently no neuroanatomical biomarkers of anorexia nervosa (AN) available to make clinical inferences at an individual subject level. We present results of a multivariate machine learning (ML) approach utilizing structural neur...