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19th Annual ieee International conference on bioinformatics and Bioengineering (BIBE)

作者： Christodoulou, Christiana C. Minadakis, George Demetriou, Christiana A. Zamba-Papanicolaou, Eleni Spyrou, George M. Cyprus Inst Neurol & Genet Neurol Clin & Bioinformat Grp Engomi Cyprus Cyprus Sch Mol Med Engomi Cyprus Cyprus Inst Neurol & Genet Bioinformat Grp Engomi Cyprus Univ Nicosia Sch Med Dept Primary Care & Populat Engomi Cyprus

ISBN: (纸本)9781728146171

Huntington's disease (HD), a rare autosomal dominant disease, affecting the medium spiny neurons of the CNS. Although HD is caused by a trinucleotide repeat in the HTT gene, it is a complex disease. systems bioinformatics which combines systems biology and bioinformatics, has the ability to reveal synergistic relationships between multiple entities. This approach is vital as it can shed light on the biological behavior and mechanisms of the cell rather than only trying to study and understand a part of the system. Metabolomics is the systematic study and measurement of metabolites within a biological sample. In this work, we employ two approaches to identify metabolites for HD-related pathways, which were previously identified from our previous work on multi-source data integration These include: i) creation of pathway-to-pathway networks based on the reference network of PathwayConnector where pathways are mapped based on connectivity on KEGG, and (ii) creation of pathway-to-pathway networks using a pairwise approach, where a connection between two pathways exists only if they share common metabolites.

关键词： Huntington's disease Metabolomics systems bioinformatics PathwayConnector

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Guest Editors' Introduction to the Special Section on the 14th International conference on computational Methods in systems Biology (CMSB 2016)

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第4期15卷 1122-1123页

作者： Bartocci, Ezio Lio, Pietro Paoletti, Nicola Vienna Univ Technol Fac Informat Treitlstr 3 A-1040 Vienna Austria Univ Cambridge Dept Comp Sci & Technol William Gates Bldg15 JJ Thomson Ave Cambridge CB3 0FD England SUNY Stony Brook Dept Comp Sci Stony Brook NY 11794 USA

No abstract available.

关键词： Special issues and sections Meetings computational biology

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PTC: An interactive tool for phylogenetic tree construction 2

PTC: An interactive tool for phylogenetic tree construction

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2nd International computational systems bioinformatics conference

作者： Yang, C Khuri, S San Jose State Univ Dept Comp Sci San Jose CA 95192 USA

ISBN: (纸本)0769520006

A phylogenetic tree represents the evolutionary history of a group of organisms. In this work, we introduce a novel interactive tool for constructing phylogenetic trees, Phylogenetic Tree Construction package. The package supports four well-known algorithms, Unweighted Pair Group Method using Arithmetic average, Neighbor Joining, Fitch Margoliash, and Maximum Parsimony.

关键词： bioinformatics

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A Fuzzy Set Framework for Ontological Similarity Measures

A Fuzzy Set Framework for Ontological Similarity Measures

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2010 ieee World Congress on computational Intelligence

作者： Cross, Valerie V. Yu, Xinran Miami Univ Oxford OH 45056 USA

ISBN: (纸本)9781424469208

Advances in biotechnology have given rise to rapid production of biomedical data and the creation of a wide variety of biomedical and bioinformatics ontologies which serve as a primary impetus for the creation of new ontological similarity measures. A new IC ontological similarity measure, a variation of a standard fuzzy set similarity measure, is presented. This new IC ontological similarity measure has never been used in bioinformatics studies. It is compared with two standard IC ontological similarity measures, Resnik and Lin, and also an existing modification of Lin's measure by analyzing the results when used on a set of concepts pairs selected from the cellular component sub-ontology of the Gene Ontology. As part of this experiment, several different methods of calculating IC for an ontological concept are also investigated. These results for the cellular component sub-ontology confirm the results of a previous study on WordNet showing that ontology-based IC measures corresponded closely with corpus-based IC measures.

关键词： IC ontological similarity measure Lin measure Resnik measure WordNet bioinformatics bioinformatics ontology biomedical data biotechnology cellular component fuzzy set fuzzy set theory gene ontology ontologies (artificial intelligence)

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Guest Editorial for Special Section on the 12th International conference on Intelligent Computing (ICIC)

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第5期15卷 1433-1435页

作者： Huang, De-Shuang Bevilacqua, Vitoantonio Gromiha, M. Michael Tongji Univ Machine Learning & Syst Biol Lab Shanghai 201804 Peoples R China Polytech Bari Elect & Informat Engn Dept I-70126 Bari BA Italy Indian Inst Technol IIT Madras Dept Biotechnol Madras 600036 Tamil Nadu India

The eight papers included in this special section were presented at the 12th International conference on Intelligent Computing (ICIC) held at Lanzhou, China, during August 2-5, 2016. ICIC was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the multifaceted aspects of intelligent computing.

关键词： Special issues and sections Meetings bioinformatics Machine learning Intelligent systems

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Guest Editorial for Special Section on the 11th International conference on Intelligent Computing (ICIC)

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2017年第5期14卷 1104-1105页

作者： Huang, De-Shuang Bevilacqua, Vitoantonio Gromiha, M. Michael Tongji Univ Machine Learning & Syst Biol Lab Shanghai Peoples R China Polytech Bari Elect & Informat Engn Dept I-70126 Bari Italy Indian Inst Technol Dept Biotechnol Madras 600036 Tamil Nadu India

The papers in this special section were presented at the 11th International conference on Intelligent Computing ICIC held in Fuzhou, China, on August 20-23, 2015. This conference was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, etc. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the multifaceted aspects of intelligent computing.

关键词： Special issues and sections Artificial intelligence Machine learning bioinformatics Biomedical engineering Predictive models Intelligent systems

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An information fusion approach to controlling complexity in bioinformatics research

An information fusion approach to controlling complexity in ...

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2005 ieee computational systems bioinformatics conference, Workshops and Poster Abstracts

作者： Olsson, Björn Nilsson, Patrie Gawronska, Barbara Persson, Anne Ziemke, Tom Andler, Sten F. School of Humanities and Informatics University of Skövde SE-54128 Skövde Sweden School of Life Sciences University of Skövde SE-54128 Skövde Sweden School of Technology and Society University of Skövde SE-54128 Skövde Sweden

ISBN: (纸本)0769524427

Information Fusion (IF) is about combining, or fusing, information from different sources in order to facilitate our understanding of a complex system and thereby provide insights that could not be gained from any of the individual data sources in isolation. We argue in this paper that there is a need for applying an IF approach in bioinformatics research, since the aim of bioinformatics is to understand complex biological systems using many different data sources providing complementary views of the system. We illustrate this argument with two application examples, where IF-based bioinformatics is applied to the study of stem cell differentiation and lipid digestion, respectively. We also discuss the use of automated information extraction from text sources, which is an essential component of a bioinformatics IF approach, given the abundant literature. © 2005 ieee.

关键词： Sensor data fusion

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Predicting Time Sequences in Gene Expression Using Dynamic Neuro-Fuzzy Networks

Predicting Time Sequences in Gene Expression Using Dynamic N...

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ieee conference on computational Intelligence in bioinformatics and computational Biology CIBCB

作者： Ahmadi, Ali Tari, Sadaf Iranpour KN Toosi Univ Technol Fac Comp Engn Tehran Iran

ISBN: (纸本)9781479969265

Gene regulation at the cellular level is a dynamic process;and neural networks with the capability of being trained and regulated based on training data, and fuzzy systems with their interpretability, are suitable algorithms for this type of computations. In this research, methods based on neuro-fuzzy networks were employed for predicting the complicated relationships that exist among genes. In the proposed method, genes that have the greatest effect on each other are found and considered as regulatory genes. Then the types of their relationships including those with inhibitory, activating, and neutralizing effects are determined, and the gene regulatory network is mapped. The standard microarray dataset related to 12 typical genes that influence the germination cycle of the yeast species Saccharomyces cerevisiae was used for training. Obtained results were validated using previous biological laboratory results. It was found that the proposed method reduced the number of extracted rules for input-output space fragmentation by 15%, which substantially reduced the required computations, while the sum square error of the algorithm declined by -0.3 compared to the method that resembled the proposed algorithm the most.

关键词： bioinformatics gene expression gene regulatory network neuro-fuzzy networks

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Using Clouds for Metagenomics: A Case Study

Using Clouds for Metagenomics: A Case Study

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ieee International conference on Cluster Computing (Cluster 2009)

作者： Wilkening, Jared Wilke, Andreas Desai, Narayan Meyer, Folker Argonne Natl Lab Div Math & Comp Sci Argonne IL 60439 USA

ISBN: (纸本)9781424450114

Cutting-edge sequencing systems produce data at a prodigious rate;and the analysis of these datasets requires significant computing resources. Cloud computing provides a tantalizing possibility for on-demand access to computing resources. However, many open questions remain. We present here a performance assessment of BLAST on real metagenomics data in a cloud setting, in order to determine the viability of this approach. BLAST is one of the premier applications in bioinformatics and computational biology and is assumed to consume the vast majority of resources in that area.

关键词： bioinformatics

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Intelligent Mobile Web Service for bioinformatics systems

Intelligent Mobile Web Service for Bioinformatics Systems

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International conference on Informative and Cybernetics for computational Social systems (ICCSS)

作者： Chuang, Chen-Chia Jeng, Jin-Tsong Hsiao, Chih-Ching Ho, Yu-Yang Liu, Yue-Shiang Natl Ilan Univ Dept Elect Engn Yilan 260 Taiwan Kao Yuan Univ Dept Informat Technol Kaohsiung Taiwan Natl Formosa Univ Dept Comp Sci & Informat Engn Huwei Township Yunlin Taiwan

ISBN: (纸本)9781467372459

In this paper, to integrate android systems, intelligent computing and web service on an intelligent mobile web service computing systems for bioinformatics is proposed. That is, users can send parameters to control the intelligent computing system under Matlab/C#/Java and query from client-side to server-side in the proposed bioinformatics systems with their android phone. Besides, the proposed system can also deal with disease genes search under web service with bioinformatics web. At the same time, web service is important communication protocol in the proposed systems. Consequently, the proposed systems can provide that user can modify parameters for controlling the proposed intelligent computing, deal with disease genes search under web service with bioinformatics web and obtain results from the proposed systems by android phone arbitrarily.

关键词： Android systems Web Service bioinformatics mobile computing

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