<html><head><meta http-equiv="Content-Type" content="text/html; charset=utf-8"></head><body style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><meta http-equiv="Content-Type" content="text/html; charset=utf-8" class=""><div style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class=""><meta http-equiv="Content-Type" content="text/html; charset=utf-8" class=""><div style="word-wrap: break-word; -webkit-nbsp-mode: space; line-break: after-white-space;" class="">Fellow Colleagues,<div class="">following the experience of the previous edition, we propose our Special Session on Computational Intelligence for Bioinformatics and Computational Biology also at IEEE WCCI 2020 (Glasgow, UK).</div><div class=""><br class=""></div><div class=""><br class=""></div><div class="">Bioinformatics and Computational Biology deal with a wide range of problems and applications which, in recent years, have been successfully solved by means of Computational Intelligence and Machine Learning techniques. Moreover, due to technological progress, huge amounts of data concerning biological organisms are gathered and collected (e.g. genes transcript, protein structures and the like), thereby demanding the use of parallel and distributed computing for facing Big Datasets and/or high-throughput application requirements. Further, in such fields, data usually encodes complex information, which is natively represented by structured records, such as sequences, graphs and images, most of which lie in so-called “non-metric spaces”, i.e. input spaces for which a meaningful (dis)similarity measure might not be metric, making the problem more challenging since ad-hoc (dis)similarity measures or embedding functions need to be defined.<br class=""><br class="">This Special Session aims at collecting the latest research in Computational Intelligence applications for Bioinformatics and Computational Biology, with emphasis on parallel/distributed computing and non-metric spaces analysis, by means of different (or hybridization of) Computational Intelligence techniques, from evolutionary meta-heuristics to neural computation, from pattern recognition to fuzzy systems.</div><div class=""><br class=""></div><div class="">Topics of interest include (but are not limited to):<br class=""><br class=""><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Network and Systems Biology<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Gene expression, gene regulatory networks<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Sequence analysis, alignment and comparison<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Biological complex systems modelling<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Predictive medicine and medical image analysis<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Network medicine<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Large-scale data mining and pattern recognition<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Distributed and parallel computing systems for machine learning and data mining<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Network generative models<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Graph kernels and string kernels in biology<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Exact/inexact motifs and pattern matching<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Granular computing approaches for non-metric space analysis<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Protein folding/function prediction<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• Analysis of metabolic pathways<br class=""></div><div class=""><span class="Apple-tab-span" style="white-space:pre"> </span>• RNA/protein structure prediction</div></div><div class=""><br class=""></div><div class="">More info here: <a href="https://sites.google.com/a/uniroma1.it/wcci2020-ci4bcb/home" class="">https://sites.google.com/a/uniroma1.it/wcci2020-ci4bcb/home</a></div><div class=""><br class=""></div><div class="">Needless to say, you are all invited to join.</div><div class=""><br class=""></div><div class="">King regards</div><div class=""><br class=""><div class="">
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font-size: 10px; line-height: 12px; color: rgb(33, 33, 33); margin-bottom: 10px;" class=""><span style="font-weight: bold;" class="">Alessio Martino</span><span class="Apple-converted-space"> </span>/<span class="Apple-converted-space"> </span>PhD Research Fellow<span class="Apple-converted-space"> </span><br class=""><a href="mailto:alessio.martino@uniroma1.it" style="color: rgb(71, 124, 204); text-decoration: none; display: inline;" class="">alessio.martino@uniroma1.it</a></p><p style="font-family: Helvetica, Arial, sans-serif; font-size: 10px; line-height: 12px; margin-bottom: 10px;" class=""><span style="font-weight: bold; color: rgb(33, 33, 33);" class="">Department of Information Engineering, Electronics and Telecommunications (DIET) - University of Rome "La Sapienza"</span><span class="Apple-converted-space"> </span><br class=""><span style="color: rgb(33, 33, 33);" class=""></span><span style="color: rgb(33, 33, 33);" class=""></span><span style="color: rgb(33, 33, 33);" class="">Via Eudossiana 18</span><span style="display: block;" class=""></span><span style="color: rgb(33, 33, 33);" class="">00184 Rome, Italy</span><span class="Apple-converted-space"> </span><br class=""><a href="https://web.uniroma1.it/dip_diet/en" style="color: rgb(71, 124, 204); 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