Ferret 发表于 2025-3-21 18:17:06
书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0317898<br><br> <br><br>书目名称Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0317898<br><br> <br><br>Anticoagulant 发表于 2025-3-21 22:39:50
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 发表于 2025-3-22 01:09:32
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 constraintascend 发表于 2025-3-22 04:48:06
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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 liesstratum-corneum 发表于 2025-3-22 15:54:55
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 regimstratum-corneum 发表于 2025-3-22 19:42:31
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 methodinsightful 发表于 2025-3-22 23:27:24
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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 发表于 2025-3-23 09:18:00
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