Titlebook: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics; 9th European Confere Clara Pizzuti,Marylyn D. Ritchie,Mario G

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書(shū)目名稱Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics影響因子(影響力)




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書(shū)目名稱Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics讀者反饋




書(shū)目名稱Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics讀者反饋學(xué)科排名

Anticoagulant

A New Evolutionary Gene Regulatory Network Reverse Engineering Tooling genetic programming, it extracts the activation functions of the different genes from those data. Successively, the gene regulatory network is reconstructed exploiting the automatic feature selection performed by genetic programming and its dynamics can be simulated using the previously extracte

大笑

ML-Consensus: A General Consensus Model for Variable-Length Transcription Factor Binding Sitesranscription factor (TF) binding sites (TFBS). Examples include all binding sites being of equal length, or having exactly one core region with fixed format, etc. In this paper, we have constructed a generalized consensus model (called Mixed-Length-Consensus, or ML-Consensus) without such constraint

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ATHENA Optimization: The Effect of Initial Parameter Settings across Different Genetic Modelsor this type of data is the genome-wide association study (GWAS) where each variation is assessed individually for association to disease. While these studies have elucidated novel etiology, much of the variation due to genetics remains unexplained. One hypothesis is that some of the variation lies

stratum-corneum

Validating a Threshold-Based Boolean Model of Regulatory Networks on a Biological Organismetwork of a plant, along with the Boolean update functions attached to each element, to validate a previously proposed threshold-based additive update function. To do that, we determine the dynamical regime of the original system, then setup the parameters of the Boolean function to match this regim

stratum-corneum

A Nearest Neighbour-Based Approach for Viral Protein Structure Prediction This study proposes a method in which protein fragments are assembled according to their physicochemical similarities, using information extracted from known protein structures. Several existing protein tertiary structure prediction methods produce contact maps as their output. Our proposed method

insightful

CLAP

Finding Motifs in DNA Sequences Applying a Multiobjective Artificial Bee Colony (MOABC) Algorithmk of discovering novel Transcription Factor Binding Sites (TFBS) in DNA sequences. In the last years there have appeared many new evolutionary algorithms based on the collective intelligence. Finding TFBS is crucial for understanding the gene regulatory relationship but, motifs are weakly conserved,

Crohns-disease

An Evolutionary Approach for Protein Contact Map Predictionording to their importance in the folding process: hydrophobicity, polarity, charge and residue size. Our evolutionary algorithm provides a set of rules which determine different cases where two amino acids are in contact. A rule represents two windows of three amino acids. Each amino acid is charac