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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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computational identification of metabolites for pathways related to Huntington's disease 19

Computational identification of metabolites for pathways rel...

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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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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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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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Fractal Genomics modeling: A new approach to genomic analysis and biomarker discovery

Fractal Genomics modeling: A new approach to genomic analysi...

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ieee computational systems bioinformatics conference (CSB 2004)

作者： Shaw, S Shapshak, P Hlth Discovery Corp Inc Savannah GA 31406 USA

ISBN: (纸本)0769521940

Reverse engineering of genetic networks generally requires establishing correlative behavior within and between a very large number of genes. This becomes a difficult analytical problem for even a few hundred genes and the difficulty tends to grow exponentially as more genes are examined Using a hybrid data analysis method known as Fractal Genomics Modeling (FGM), this problem is reduced to examining correlative behavior within small gene groups that can then be compared and integrated to produce a picture of larger networks using a type of shotgun approach. We have applied FGM toward examining genetic networks involved in HIV infection in the brain. These networks have relevance both to processes related to HIV infection and neurodegenerative disorders. Our preliminary findings have produced conjectures of related pathways and networks as well new candidates for genetic markers in HIV brain infection. Evidence has also been produced which appears to show the presence of a hierarchical network structure within the genes studied We will discuss the background and methodology of FGM as well as our recent findings.

关键词： bioinformatics gene expression fractals network theory scale-free brain HIV infection

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IAS: Interaction Specific GO Term Associations for Predicting Protein-Protein Interaction Networks

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ieee-ACM TRANSACTIONS ON computational BIOLOGY AND bioinformatics 2018年第4期15卷 1247-1258页

作者： Yerneni, Satwica Khan, Ishita K. Wei, Qing Kihara, Daisuke Mayo Clin Div Biomed Stat & Informat Rochester MN 55905 USA Purdue Univ Dept Comp Sci W Lafayette IN 47906 USA Purdue Univ Dept Biol Sci W Lafayette IN 47906 USA

Proteins carry out their function in a cell through interactions with other proteins. A large scale protein-protein interaction (PPI)network of an organism provides static yet an essential structure of interactions, which is valuable clue for understanding the functions of proteins and pathways. PPIs are determined primarily by experimental methods;however, computational PPI prediction methods can supplement or verify PPIs identified by experiment. Here, we developed a novel scoring method for predicting PPIs from Gene Ontology (GO) annotations of proteins. Unlike existing methods that consider functional similarity as an indication of interaction between proteins, the new score, named the protein-protein Interaction Association Score (IAS), was computed from GO term associations of known interacting protein pairs in 49 organisms. IAS was evaluated on PPI data of six organisms and found to outperform existing GO term-based scoring methods. Moreover, consensus scoring methods that combine different scores further improved performance of PPI prediction.

关键词： bioinformatics proteins computational systems biology biological interactions

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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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Using easel for modeling and simulating the interactions of cells in order to better understand the basics of biological processes and to predict their likely behaviors 2

Using easel for modeling and simulating the interactions of ...

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2nd International computational systems bioinformatics conference

作者： Stojkovic, V Steele, G Lupton, W MSU Baltimore MD USA

ISBN: (纸本)0769520006

Modeling, simulation, visualization, and animation play a significant role in the study of bioinformatics. Research in this area is generally multidisciplinary in nature and collaboratively conducted by researchers with expertise in biology, bioinformatics, computer science, artificial intelligence, mathematics, and statistics. Easel programming language is used for modeling, simulation, visualization, and animation of interactions of cells in order to better understand the basics of biological processes and to predict their likely behaviors. This paper presents a computer science - modeling, simulation, visualization, and animation approach to such research. The paper provides a brief overview of the basic ideas in the "Message Passing" Easel program to demonstrate the transmission of signals between cells based on their physical proximity.

关键词： bioinformatics

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