Name: Bio-Inspired Computing Models and Algorithms
Author: Tao Song, Pan Zheng;Mou Ling Dennis Wong;Xun Wang

Bio-inspired computing (BIC) focuses on the designs and developments of computer algorithms and models based on biological mechanisms and living phenomena. It is now a major subfield of natural computation that leverages on the recent advances in computer science, biology and mathematics. The ideas provide abundant inspiration to construct high-performance computing models and intelligent algorithms, thus enabling powerful tools to solve real-life problems. Written by world-renowned researchers, this compendium covers the most influential topics on BIC, where the newly-obtained algorithms, developments and results are introduced and elaborated. The potential and valuable directions for further research are addressed as well. Contents: <ul> <li>A Gentle Introduction to Membrane Systems and Their Computational Properties (Alberto Leporati, Luca Manzoni, Giancarlo Mauri, Antonio E Porreca and Claudio Zandron) </li> <li>Results on Computational Complexity in Bio-inspired Computing (Mario J P&#x00E9;rez-Jim&#x00E9;nez, Agust&#x00ED;n Riscos-N&#x00FA;&#x00F1;ez, Luis Valencia-Cabrera and David Orellana-Mart&#x00ED;n) </li> <li>Integrative Approaches for Predicting microRNA Function and Prioritizing Disease-Related microRNA Using Biological Interaction Networks (Xuan Zhang and Xiangxiang Zeng) </li> <li>Evolutionary Algorithm for Solving Complex Multiobjective Optimization Problems (Ye Tian and Xingyi Zhang) </li> <li>A Bio-inspired Clustering Model for Anomaly Detection in the Mining Industry (Raymond Chiong, Zhongyi Hu, Zongwen Fan, Yuqing Lin, Stefan Chalup and Antoine Desmet) </li> <li>Picture Generating Models Based on the Splicing Operation (K G Subramanian, G Samdanielthompson and N Gnanamalar David) </li> <li>Fingerprint Minutiae to Fixed-Length Bit-String: A Review of Recent Development (Zhe Jin, Wei-Jing Wong and Andrew Beng Jin Teoh) </li> <li>Platform for Detection of Ultra-DNA Signals (10&#x2013;18 mol/L) with DNA Probe and Nanomaterials (Xun Wang and Ben Hoo Mook) </li> <li>Deep Autoencoders in Pattern Recognition: A Survey (Junfen Chen, Bojun Xie, Hui Zhang and Junhai Zhai) </li> <li>Genetic Algorithm: From Promiscuity to Monogamy (Ting Yee Lim and Choo Jun Tan) </li></ul> Readership: Researchers, academics and professionals in artificial intelligence, neural networks, theoretical computer science, bioinformatics and biocomputing.Bio-Inspired Computing;Nature Computing;Membrane Computing;Biometric;Bioinformatics;Neural Networks;Machine Learning00

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