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ieee Symposium on computational intelligence in bioinformatics and computational biology

作者： Lee, Leong Leopold, Jennifer L. Frank, Ronald L. Maglia, Anne M. Missouri Univ Sci & Technol Dept Comp Sci Rolla MO 65409 USA Missouri Univ Sci & Technol Dept Biol Sci Rolla MO 65409 USA

ISBN: (纸本)9781424427567

With the increase of data from genome sequencing projects comes the need for reliable and efficient methods for the analysis and classification of protein motifs and domains. Experimental methods currently used to determine protein structure are accurate, yet expensive both in terms of time and equipment. Therefore, various computational approaches to solving the problem have been attempted, although their accuracy has rarely exceeded 75%.. In this paper, a rule-based method to predict protein secondary structure is presented. This method uses a newly developed data-mining algorithm called RT-RICO (Relaxed Threshold Rule Induction from Coverings), which identifies dependencies between amino acids in a protein sequence, and generates rules that can be used to predict secondary structures. The average prediction accuracy on sample data sets, or Q(3) score, using RT-RICO was 80.3%, an improvement over comparable computational methods.

关键词： computational methods

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Intellectual property protection for bioinformatics and computational biology

Intellectual property protection for bioinformatics and comp...

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5th International conference on bioinformatics and computational biology 2013, BICoB 2013

作者： Fernandez, Dennis Maninang, Antonia Kobayashi, Shumpei Fernandez and Associates LLP United States Stanford Hospital United States University of California San Diego United States

ISBN: (纸本)9781622769711

bioinformatics, and computational biology are two ever-growing fields that require careful attention to intellectual property rights (IPR) and strategies. The American patent system is currently going through the biggest reformation since the passage of Patent Act of 1952, and many changes apply directly to the field of biology that utilize computational intelligence. Basic IP definitions, recent IP developments, and advanced protection strategies are discussed in order to better understand the status quo of intellectual property (IP) specifically in the field of evolutionary computation, bioinformatics, and computational biology.

关键词： bioinformatics

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11th International conference on Practical Applications of computational biology & bioinformatics 1st ed. 2017

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丛书名： Advances in Intelligent Systems and Computing

2017年

作者： Florentino Fdez-Riverola Mohd Saberi Mohamad Miguel Rocha Juan F. De Paz Tiago Pinto

ISBN: (数字)9783319608167

ISBN: (纸本)9783319608150

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next-generation sequencing technologies, together with novel and constantly evolving, distinct types of omics data technologies, have created an increasingly complex set of challenges for the growing fields of bioinformatics and computational biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial intelligence. Clearly, biology is more and more a science of information and requires tools from the computational sciences. In the last few years, we have seen the rise of a new generation of interdisciplinary scientists with a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance in boosting the research efforts in the field and contributing to the education of a new generation of bioinformatics scientists. The PACBB17 conference was intended to contribute to this effort and promote this fruitful interaction, with a technical program that included 39 papers spanning many different sub-fields in bioinformatics and computational biology. Further, the conference promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists).

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Guest Editorial for Selected Papers From BIOKDD 2021

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2022年第6期19卷 3068-3069页

作者： Yan, Da Qin, Zhaohui S. Bhattacharya, Debswapna Chen, Jake Y. Univ Alabama Birmingham Dept Comp Sci Birmingham AL 35294 USA Emory Univ Dept Biostat & Bioinformat Atlanta GA 30322 USA Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Univ Alabama Birmingham Inst Informat Birmingham AL 35294 USA

The papers in this special section were presented at the 20th International Workshop on Data Mining in bioinformatics (BIOKDD 2021) that was held virtually on August 15, 2021. The conference featured the special theme of "Artificial intelligence in Medicine" which particularly welcomed paper submissions and invited talks related to the use of machine learning and data mining techniques for the analysis of large amounts of heterogeneous complex biological and medical data, with a particular focus on deep learning methods that see fast advancement and wider adoption in bioinformatics.

关键词： Special issues and sections Meetings bioinformatics Data mining

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Guest Editorial for Special Section on BIBM 2015

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2018年第6期15卷 1752-1753页

作者： Tian, Tianhai Huang, Jingshan Monash Univ Sch Math Sci Melbourne Vic 3800 Australia Univ S Alabama Sch Comp Shelby HallSuite 2101150 Jaguar Dr Mobile AL 36688 USA

The six papers in this special section were presented at the ieee BIBM 2015 conference that was held in Washington, D.C., November 9-12, 2015. The scientific program highlighted 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 Meetings bioinformatics Informatics Biological systems modeling Genomics computational modeling

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Codon Context Optimization in Synthetic Gene Design

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2018年第2期15卷 452-459页

作者： Papamichail, Dimitris Liu, Hongmei Machado, Vitor Gould, Nathan Coleman, J. Robert Papamichail, Georgios Coll New Jersey Dept Comp Sci 2000 Pennington Rd Ewing NJ 08628 USA Univ Miami Miller Sch Med Dept Publ Hlth Sci Div Biostat Miami FL 33136 USA Farmingdale State Coll Dept Biol Farmingdale NY 11735 USA New York Coll Dept Informat Amalias 38 Ave Athens 10558 Greece

Advances in de novo synthesis of DNA and computational gene design methods make possible the customization of genes by direct manipulation of features such as codon bias and mRNA secondary structure. Codon context is another feature significantly affecting mRNA translational efficiency, but existing methods and tools for evaluating and designing novel optimized protein coding sequences utilize untested heuristics and do not provide quantifiable guarantees on design quality. In this study we examine statistical properties of codon context measures in an effort to better understand the phenomenon. We analyze the computational complexity of codon context optimization and design exact and efficient heuristic gene recoding algorithms under reasonable constraint models. We also present a web-based tool for evaluating codon context bias in the appropriate context.

关键词： computational biology dynamic programming simulated annealing synthetic biology

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7th International conference on Practical Applications of computational biology &bioinformatics 1

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丛书名： Advances in Intelligent Systems and Computing

2013年

作者： Liliana López-Kleine, José Romeo (auth.), Mohd Saberi Mohamad, Loris Nanni, Miguel P. Rocha, Florentino Fdez-Riverola (eds.)

ISBN: (数字)9783319005782

ISBN: (纸本)9783319005775;9783319005782

The growth in the bioinformatics and computational biology fields over the last few years has been remarkable and the trend is to increase its pace. In fact, the need for computational techniques that can efficiently handle the huge amounts of data produced by the new experimental techniques in biology is still increasing driven by new advances in Next Generation Sequencing, several types of the so called omics data and image acquisition, just to name a few. The analysis of the datasets that produces and its integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial intelligence. Within this scenario of increasing data availability, Systems biology has also been emerging as an alternative to the reductionist view that dominated biological research in the last decades. Indeed, biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of bioinformatics scientists. PACBB13 hopes to contribute to this effort promoting this fruitful interaction. PACBB'13 technical program included 19 papers from a submission pool of 32 papers spanning many different sub-fields in bioinformatics and computational biology. Therefore, the conference will certainly have promoted the interaction of scientists from diverse research groups and with a distinct background (computer scientists, mathematicians, biologists). The scientific content will certainly be challenging and will promote the improvement of the work that is being developed by each of the pa

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8th International conference on Practical Applications of computational biology &bioinformatics (PACBB 2014) 1

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丛书名： Advances in Intelligent Systems and Computing

2014年

作者： Julio Saez-Rodriguez, Miguel P. Rocha, Florentino Fdez-Riverola, Juan F. De Paz Santana (eds.)

ISBN: (数字)9783319075815

ISBN: (纸本)9783319075808;9783319075815

Biological and biomedical research are increasingly driven by experimental techniques that challenge our ability to analyse, process and extract meaningful knowledge from the underlying data. The impressive capabilities of next generation sequencing technologies, together with novel and ever evolving distinct types of omics data technologies, have put an increasingly complex set of challenges for the growing fields of bioinformatics and computational biology. The analysis of the datasets produced and their integration call for new algorithms and approaches from fields such as Databases, Statistics, Data Mining, Machine Learning, Optimization, Computer Science and Artificial intelligence. Clearly, biology is more and more a science of information requiring tools from the computational sciences. In the last few years, we have seen the surge of a new generation of interdisciplinary scientists that have a strong background in the biological and computational sciences. In this context, the interaction of researchers from different scientific fields is, more than ever, of foremost importance boosting the research efforts in the field and contributing to the education of a new generation of bioinformatics scientists. PACBB14 contributes to this effort promoting this fruitful interaction. PACBB'14 technical program included 34 papers spanning many different sub-fields in bioinformatics and computational biology. Therefore, the conference promotes the interaction of scientists from diverse research groups and with a distinct background such as computer scientists, mathematicians or biologists.

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ENISI SDE: A Novel Web-based Stochastic Modeling Tool for computational biology

ENISI SDE: A Novel Web-based Stochastic Modeling Tool for Co...

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ieee International conference on bioinformatics and Biomedicine (ieee BIBM)

作者： Mei, Yongguo Carbo, Adria Hontecillas, Raquel Bassaganya-Riera, Josep Virginia Tech Virginia Bioinformat Inst Nutr Immunol & Mol Med Lab Ctr Modeling Immun Enter Pathogens Blacksburg VA 24061 USA

ISBN: (纸本)9781479913091;9781479913107

Stochasticity is part of the nature of many biological processes and an important aspect in modeling and simulations of computational biology. Gillespie's algorithm was developed for modeling stochasticity of chemical reactions and has been broadly applied to stochastic modeling in computational biology. The Gillespie's algorithm accounts for the particle effect in chemical reactions. However, many biological processes including cellular and molecular immunological mechanisms have many other sources of stochasticity such as cell movement, ligand binding, or unaccounted variation in experimental settings. In this paper, we propose stochastic differential equations (SDE) being used as a generic stochastic modeling technique for systems immunology. SDE has been widely used in statistics and economics areas;but only a few isolated studies in computational biology are found using SDE to model stochastic behaviors of cells and molecules. In addition, to the best of our knowledge, there is no user-friendly SDE-based modeling tool available for computational biologists. This paper presents ENISI SDE, a web-based user-friendly stochastic modeling tool for computational biologists. This work provides three major contributions: (1) we discuss SDE and propose it as a generic approach for stochastic modeling in computational biology;(2) we develop ENISI SDE, a web-based user-friendly SDE modeling tool that only requires little extra effort beyond regular ODE-based modeling;(3) we use the model SDE modeling tool to study stochastic sources of cell heterogeneity in the context of a CD4+ T Cell differentiation process. The case study clearly shows the effectiveness of SDE as a stochastic modeling approach in biology in general and immunology in particular and the power of the SDE modeling tool we developed.

关键词： Immunology

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Guest Editorial for Selected Papers from BIOKDD 2018 and DMBIH 2018

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ieee-ACM TRANSACTIONS ON computational biology AND bioinformatics 2020年第6期17卷 1832-1834页

作者： Yan, Da Gao, Xin Fodeh, Samah J. Chen, Jake Y. Univ Alabama Birmingham Dept Comp Sci 4105 Univ Hall1402 10th Ave South Birmingham AL 35294 USA King Abdullah Univ Sci & Technol KAUST Computat Biosci Res Ctr Comp Elect & Math Sci & Engn Div Thuwal 23955 Saudi Arabia Jarad Yale Sch Med Ctr Healthcare Innovat Redesign & Learning CHIRAL New Haven CT 06510 USA Univ Alabama Birmingham PhD Informat Inst 1900 Univ BlvdTHT 1st Floor Birmingham AL 35233 USA

The papers in this special issue were presented at the 2018 17th International Workshop on Data Mining in bioinformatics (BIOKDD), held in conjunction with the ACM SIGKDD International conference on Knowledge Discover... 详细信息

关键词： Special Issues And Sections bioinformatics Data Mining computational biology Meetings

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