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ieee TRANSACTIONS ON NANOBIOSCIENCE 2015年第5期14卷 498-499页

作者： Hu, Xiaohua Wang, Yadong Drexel Univ Philadelphia PA 19104 USA Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Peoples R China

The papers in this special section were presented at the ieee BIBM 2014 conference that was held in Belfast, U.K., from November 18–22, 2014. The scientific program highlights five themes to provide breadth, depth, and synergy for research collaboration: 1) genomics and molecular structure, function, and evolution; 2) computational systems biology; 3) medical informatics and translational bioinformatics; 4) cross-cutting computational methods and bioinformatics infrastructures; and 5) healthcare informatics.

关键词： Special issues and sections Informatics bioinformatics Genomics Evolution (biology) computational systems biology Meetings

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Analysis of Gene Variants for Functional Annotations 16

Analysis of Gene Variants for Functional Annotations

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16th ieee International conference on computational intelligence in bioinformatics and computational biology (ieee CIBCB)

作者： Al-Mubaid, Hisham Univ Houston Clear Lake Dept Comp Sci Houston TX 77058 USA

ISBN: (纸本)9781728114620

The study and analysis of functional annotations of human genes and gene variants are important for understanding functional genomics and gene-disease associations. This paper investigates the process of functional annotation of gene variants using the gene ontology. The paper also presents a method for annotating gene variants with biological process terms from the gene ontology. The presented method relies on identifying the enriched biological processes of the genes associated with the given genetic variants. With significant level of p<0.02, the results found to be biologically significant. Furthermore, we found that certain ontology annotations e.g. {GO:0031325;positive regulation of cellular metabolic process} are more connected with mutations via certain genes compared with normal biological process terms in the gene ontology.

关键词： Diseases Genomics bioinformatics Ontologies Biological processes DNA

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Guest Editorial for Special Section on the 14th International conference on Intelligent Computing (ICIC)

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2020年第5期17卷 1474-1475页

作者： Huang, De-Shuang Bevilacqua, Vitoantonio Gromiha, Michael Tongji Univ Instute Machine Learning & Syst Biol Shanghai 201804 Peoples R China Polytech Bari Elect & Elect Dept Via Orabona I-70126 Bari BA Italy Indian Inst Technol IIT Dept Biotechnol Madras Tamil Nadu India

The papers in this special section were presented at the Fourteenth International conference on Intelligent Computing (ICIC) held in Wuhan, China, on August 15-18, 2018.

关键词： Special issues and sections computational intelligence Machine learning bioinformatics computational biology

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A Comparison of Novel Representations for Evolving Epidemic Networks

A Comparison of Novel Representations for Evolving Epidemic ...

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18th ieee International conference on computational intelligence in bioinformatics and computational biology (ieee CIBCB)

作者： Ashlock, Daniel Dube, Michael Univ Guelph Dept Math & Stat Guelph ON Canada Univ Guelph Bioinformat Program Guelph ON Canada

ISBN: (纸本)9781665401128

Recent work in representation has developed small, evolvable structures called a complex string generator that generate infinite, aperiodic strings of characters. Such a string can be sectioned to provide an arbitrary list of parameters of indefinite length. Other work in evolving networks to model disease transmission has an issue common in many high-dimensional problems, evolution is less efficient when it must get a large number of parameter values correct. Specifying many parameters with a small evolvable object is a potential solution to this problem. In this study we compare three different implementations of representations, two of which employ complex string generators, to specify social contact graphs that plausibly explain the pattern of infection in a small epidemic. Representations that edit a starting network are found to have results that clump in network space while evolving the adjacency matrix provides increased diversity: none of the representations overlap in their results. The adjacency matrix based representation also generated outliers that outperform a baseline representation, probably because of its enhance diversity of solutions.

关键词： Epidemics Evolution (biology) conferences Generators Cultural differences bioinformatics computational intelligence

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Algorithms for computational biology: Third Edition

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2019年第3期16卷 701-702页

作者： Martin-Vide, Carlos Vega-Rodriguez, Miguel A. Rovira & Virgili Univ Tarragona Spain Univ Extremadura Escuela Politecn Caceres Spain

The papers in this special section were presented at the 3rd International conference on Algorithms for computational biology, AlCoB 2016, that was held in Trujillo, Spain, on June 21- 22, 2016.

关键词： Special issues and sections Meetings bioinformatics computational biology Algorithms

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Genetic Algorithm for Optimizing Global Alignment of Protein-Protein Interaction Network 16

Genetic Algorithm for Optimizing Global Alignment of Protein...

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16th ieee International conference on computational intelligence in bioinformatics and computational biology (ieee CIBCB)

作者： Baker, Qanita Bani Al-Bataineh, Manar K. Jordan Univ Sci & Technol Dept Comp Sci Irbid Jordan

ISBN: (纸本)9781728114620

Protein-protein interactions can be modeled as networks. The huge amount of produced Protein-Protein Interaction (PPI) data has many applications in biological studies. These studies improved human knowledge in the life process and diseases. One of these studies is PPI network alignment, which finds the similarity between PPI networks as a biological similarity. Aligning these networks is important to investigate evolutionary pathways or protein complexes. The main challenge of all global PPI network alignment is to improve both accuracy and efficiency. In this research, the accuracy and efficiency of global PPI network alignment are improved by using the genetic algorithm instead of the greedy algorithm and applied in HubAlign framework. The performance of the proposed method is compared with HubAlign based on the total execution time for the alignment process and the correctness of the results of the aligned networks. The new approach enhanced the overall accuracy and reduce execution time compared to the HubAlign approach.

关键词： Protein-Protein Interaction Network Optimization bioinformatics Genetic Algorithm

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One Moose, Two Moose, Three Fields, More?

One Moose, Two Moose, Three Fields, More?

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18th ieee International conference on computational intelligence in bioinformatics and computational biology (ieee CIBCB)

作者： Ashlock, Daniel Brown, Joseph Alexander Houghten, Sheridan Makhmutov, Munir Univ Guelph Math & Stat Guelph ON Canada Innopolis Univ Artificial Intelligence Games Dev Lab Innopolis Russia Brock Univ Comp Sci St Catharines ON Canada

ISBN: (纸本)9781665401128

This study introduces a new game that models competition in foraging behavior. Two moose decide, in each time period, which of three foraging areas to visit. Moose in the same foraging area fight, gaining no forage and also damaging some forage during their conflict. Moose alone in a foraging area eat, with the forage in each field being replenished with a logistic growth model. This creates a relatively complex game with a rich strategy space in which the moose try to maximize their forage intake. The game is a coordination game, as the moose try to avoid conflict which does not maximize forage intake. The paper reports the results of two student competitions at Innopolis University and performs agent evolution to verify the existence of a rich strategy space for the game.

关键词： Game Theory Intraspecific Competition Coordination Game

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Intellectual Property Protection for bioinformatics and computational intelligence

Intellectual Property Protection for Bioinformatics and Comp...

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10th Annual ieee Symposium on computational intelligence in bioinformatics and computational biology (CIBCB)

作者： Fernandez, Dennis Maninang, Antonia Kobayashi, Shumpei Fernandez & Associates LLP Atherton CA 94027 USA Stanford Hosp Stanford CA 94305 USA Univ Calif San Diego La Jolla CA 92093 USA

ISBN: (纸本)9781467358750

bioinformatics and computational biology are two fast-growing fields that require the direct application of computational intelligence. The American patent system is currently going through the biggest reformation since the passage of Patent Act of 1952, and thus intellectual property rights (IPR) and strategies continue to be increasingly vital in these fields. In order to better understand the status quo of intellectual property (IP) specifically in the fields of biology that apply computational intelligence, basic IP definitions, recent IP developments, and advanced protection strategies are presented and discussed.

关键词： computational biology bioinformatics Intellectual Property America Invents Act Patent Portfolio

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A Note On Population Size Inspired By The Extinction Of Mammoths

A Note On Population Size Inspired By The Extinction Of Mamm...

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ieee conference on computational intelligence in bioinformatics and computational biology (CIBCB)

作者： Ashlock, Daniel Ashlock, Wendy Univ Guelph Dept Math & Stat Guelph ON N1G 2W1 Canada Ashlock & McGuinness Consulting 41 Lambert Cr Guelph ON N1G 2R4 Canada

ISBN: (纸本)9781467389884

This study performs simulations inspired by the reported genome meltdown of a small population of woolly mammoths prior to their extinction. These simulations test the interaction of population size, mutational diameter, and fitness change on two types of fitness landscapes. The first landscape studies a population initialized at a global optimum to assess fitness loss, while the second uses an open-ended function with no global optimum to assess the degree of adaptive radiation possible with different population sizes. Both an age structured non-elitist evolutionary algorithm and a evolutionstrategy like biased random walk are used. The simulations demonstrate that small populations are substantially worse at retaining fitness when initialized in a global optimum but also have a substantially greater potential for adaptive radiation and discovery of new niches.

关键词： Sociology Statistics Evolutionary computation Adaptation models Genomics bioinformatics

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Compression of Biological Networks using a Genetic Algorithm with Localized Merge 16

Compression of Biological Networks using a Genetic Algorithm...

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16th ieee International conference on computational intelligence in bioinformatics and computational biology (ieee CIBCB)

作者： Houghten, Sheridan Romualdo, Angelo Collins, Tyler K. Brown, Joseph Alexander Brock Univ Dept Comp Sci St Catharines ON Canada Innopolis Univ Artif Intelligence Games Dev Lab Innopolis Russia

ISBN: (纸本)9781728114620

Network graphs appear in a number of important biological data problems, recording information relating to protein-protein interactions, gene regulation, transcription regulation and much more. These graphs are of such a significant size that they are impossible for a human to understand. Furthermore, the ever-expanding quantity of such information means that there are storage issues. To help address these issues, it is common for applications to compress nodes to form supernodes of similarly connected components. In previous graph compression studies it was noted that such supernodes often contain points from disparate parts of the graph. This study aims to correct this flaw by only allowing merges to occur within a local neighbourhood rather than across the entire graph. This restriction was found to not only produce more meaningful compressions, but also to reduce the overall distortion created by the compression for two out of three biological networks studied.

关键词： Genetic algorithms Biological cells Sociology Statistics Proteins Merging

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