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Congress on Evolutionary Computation

作者： Kelvin Xi Zhang B.F. Francis Ouellette Ontario Institute for Cancer Research Toronto ONT Canada Graduate Program in Bioinformatics University of British Columbia BC Canada

Protein-protein interactions (PPIs) play an extremely important role in performing a variety of biological functions. The interactomes of several model organisms including budding yeast Saccharomyces cerevisiae have recently been studied using experimental techniques such as the yeast two-hybrid assay. However, these techniques are generally biased against integral membrane proteins due to their intrinsic limitations. Given the fact that the interactions between integral membrane proteins cover a large fraction of the whole interactome, we report a study of predicting interactions between integral membrane proteins in yeast by a quantitative model We integrate protein-protein interaction and domain-domain interaction (DDI) data from disparate sources and apply a log likelihood scoring method on all putative integral membrane proteins in yeast to predict their interactions based on a cut-off threshold. We show that our approach improves on other predictive approaches when tested on a ldquogold-standardrdquo data set and achieves 74.6% true positive rate at the expense of 0.43% false positive rate. Furthermore, we find that two integral membrane proteins are more likely to interact with each other if they share more common interaction partners. This study allows us to reach a more extensive understanding of the yeast integral membrane proteins from a network view, which also complements the previous prediction approaches based on the genomic context.

关键词： Evolutionary computation

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Large-scale analysis of human heavy chain V(D)J recombination patterns

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Immunome Research 2008年第1期4卷 1-10页

作者： Volpe, Joseph M Kepler, Thomas B Center for Computational Immunology Duke University Durham NC United States Department of Immunology Duke Univeristy Medical Center Durham NC United States Department of Biostatistics and Bioinformatics Duke Univeristy Medical Center Durham NC United States Institute of Statistics and Decision Sciences Duke Univeristy Durham NC United States Computational Biology and Bioinformatics Graduate Program Institute for Genome Sciences and Policy Duke Univeristy Durham NC United States

Background. The processes involved in the somatic assembly of antigen receptor genes are unique to the immune system and are driven largely by random events. Subtle biases, however, may exist and provide clues to the molecular mechanisms involved in their assembly and selection. Large-scale efforts to provide baseline data about the genetic characteristics of immunoglobulin (Ig) genes and the mechanisms involved in their assembly have recently become possible due to the rapid growth of genetic databases. Results. We gathered and analyzed nearly 6,500 productive human Ig heavy chain genes and compared them with 325 non-productive Ig genes that were originally rearranged out of frame and therefore incapable of being biased by selection. We found evidence for differences in n-nucleotide tract length distributions which have interesting interpretations for the mechanisms involved in n-nucleotide polymerization. Additionally, we found striking statistical evidence for pairing preferences among D and J segments. We present a statistical model to support our hypothesis that these pairing biases are due to multiple sequential D-to-J rearrangements. Conclusion. We present here the most precise estimates of gene segment usage frequencies currently available along with analyses regarding n-nucleotide distributions and D-J segment pair preferences. Additionally, we provide the first statistical evidence that sequential D-J recombinations occur at the human heavy chain locus during B-cell ontogeny with an approximate frequency of 20%.

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Developmental systems biology flourishing on new technologies

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Journal of Genetics and Genomics 2008年第10期35卷 577-584页

作者： Jing-Dong J. Han Yi Liu Huiling Xue Kai Xia Hong Yu Shanshan Zhu Zhang Chen Wei Zhang Zheng Huang Chunyu Jin Bo Xian Jing Li Lei Hou Yixing Han Chaoqun Niu Timothy C. Alcon Chinese Academy of Sciences Key Laboratory of Molecular Developmental Biology Center for Molecular Systems Biology Institute of Genetics and Developmental Biology Chinese Academy of Sciences Beijing 100101 China Key Laboratory of Machine Perception （Ministry of Education） Peking University Beijing 100871 China Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA 50011-1040 USA

Organism development is a systems level process. It has benefited greatly from the recent technological advances in the field of systems biology. DNA microarray, phenome, interactome and transcriptome mapping, the new generation of deep sequencing technologies, and faster and better computational and modeling approaches have opened new frontiers for both systems biologists and developmental biologists to reexamine the old developmental biology questions, such as pattern formation, and to tackle new problems, such as stem cell reprogramming. As showcased in the International Developmental Systems Biology Symposium organized by Chinese Academy of Sciences, developmental systems biology is flourishing in many perspectives, from the evolution of developmental systems, to the underlying genetic and molecular pathways and networks, to the genomic, epigenomic and noncoding levels, to the computational analysis and modeling. We believe that the field will continue to reap rewards into the future with these new approaches.

关键词： developmental systems biology new technologies symposium

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Using a literature-based NMF model for discovering gene functional relationships

Using a literature-based NMF model for discovering gene func...

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IEEE International Conference on bioinformatics and Biomedicine Workshops (BIBMW)

作者： Elina Tjioe Michael Berry Ramin Homayouni Genome Science and Technology Graduate School University of Tennessee Knoxville TN USA Department of Electrical Engineering and Computer Science University of Tennessee Knoxville TN USA Bioinformatics Program Department of Biology University of Memphis Memphis TN USA

The rapid growth of the biomedical literature and genomic information presents a major challenge for determining the functional relationships among genes. In this study, we develop a Web-based bioinformatics software environment called FAUN or feature annotation using nonnegative matrix factorization (NMF) to facilitate both the discovery and classification of functional relationships among genes. Both the computational complexity and parameterization of NMF for processing gene sets are discussed. We tested FAUN on three manually constructed gene document collections, and then used it to analyze several microarray-derived gene sets obtained from studies of the developing cerebellum in normal and mutant mice. FAUN provides utilities for collaborative knowledge discovery and identification of new gene relationships from text streams and repositories (e.g., MEDLINE). It is particularly useful for the validation and analysis of gene associations suggested by microarray experimentation.

关键词： bioinformatics Genomics Data mining Matrix decomposition Large scale integration Feature extraction Iterative methods Biological system modeling Computer science Computational biology

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Study on the immobilization of Ni-NTA and NTA on PMMA substrate base

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Key Engineering Materials 2008年 381-382卷 357-360页

作者： Chong, W.S. Kim, G.B. Hong, C.U. Department of Biomedical Engineering Graduate School Chonbuk National University Duckjin-Dong Jeonju Jeonbuk 561-756 Korea Republic of Education Program for 21st Century Chonbuk National University Research Institute of Clinical Medicine Duckjin-Dong Jeonju Jeonbuk 561-756 Korea Republic of Division of Bionics and Bioinformatics Collage of Engineering Chonbuk National University Duckjin-Dong Jeonju Jeonbuk 561-756 Korea Republic of

In this study, we attempts to develop a sensing method to detect mismatched DNA in order to diagnose cancer. The sensing method will be developed to use for early diagnosis of cancer. Thus, protein immobilization was applied on the surface of the sensor in order to facilitate the detection of mismatched DNA. This method was designed to achieve the Ni-His-Tag to selectively bond with MutS, which has a covalent bond with the His-Tag, by using Ni-NTA. This method is troublesome because it involves a number of repeated composition processes. This method need gold surface to immobilize NTA (nitrotriamino acid). But this process is very complicated and expensive cost. Therefore, we try to immobilize NTA using PMMA (poly methyl methacrylate) polymer in this research to improve this method. In this study revealed that we could directly immobilize the NTA to the PMMA substrate not used Gold substrate. Also, we could directly immobilize the MutS to the NTA using the EDC solution. In addition, we can expect that the mismatched DNA can be detected from the results.

关键词： Proteins

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Unexpected failure rates for modular assembly of engineered zinc fingers (vol 5, pg 374, 2008)

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NATURE METHODS 2008年第6期5卷 575-575页

作者： Ramirez, Cherie L. Foley, Jonathan E. Wright, David A. Mueller-Lerch, Felix Rahman, Shamim H. Cornu, Tatjana I. Winfrey, Ronnie J. Sander, Jeffry D. Fu, Fengli Townsend, Jeffrey A. Cathomen, Toni Voytas, Daniel F. Joung, J. Keith These authors contributed equally to this work. These authors contributed equally to this work. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Interdepartmental Graduate Program in Bioinformatics and Computational Biology 2114 Molecular Biology Building Iowa State University Ames Iowa 50011 USA. Interdepartmental Graduate Program in Bioinformatics and Computational Biology 2114 Molecular Biology Building Iowa State University Ames Iowa 50011 USA. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Charité Medical School Institute of Virology Hindenburgdamm 27 D-12203 Berlin Germany. Department of Genetics Development and Cell Biology Iowa State University 1035A Roy J. Carver Co-Lab Ames Iowa 50011 USA. Department of Pathology Harvard Medical School Boston Massachusetts 02115 USA.

A letter to the editor is presented in response to an article on zinc fingers in a previous issue.

关键词： LETTERS to the editor ZINC

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Evolving hypernetwork classifiers for microRNA expression profile analysis

Evolving hypernetwork classifiers for microRNA expression pr...

引用

2007 IEEE Congress on Evolutionary Computation, CEC 2007

作者： Kim, Sun Kim, Soo-Jin Zhang, Byoung-Tak Center for Bioinformatics Technology Graduate Program in Bioinformatics Seoul National University Seoul 151-742 Korea Republic of School of Computer Science and Engineering Seoul National University Seoul 151-744 Korea Republic of

ISBN: (纸本)1424413400

High-throughput microarrays inform us on different outlooks of the molecular mechanisms underlying the function of cells and organisms. While computational analysis for the microarrays show good performance, it is still difficult to infer modules of multiple co-regulated genes. Here, we present a novel classification method to identify the gene modules associated with cancers from microarray data. The proposed approach is based on 'hypernetworks', a hypergraph model consisting of vertices and weighted hyperedges. The hypernetwork model is inspired by biological networks and its learning process is suitable for identifying interacting gene modules. Applied to the analysis of microRNA (miRNA) expression profiles on multiple human cancers, the hypernetwork classifiers identified cancer-related miRNA modules. The results show that our method performs better than decision trees and naive Bayes. The biological meaning of the discovered miRNA modules has been examined by literature search. © 2007 IEEE.

关键词： Microarrays

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Finding cancer-related gene combinations using a molecular evolutionary algorithm

Finding cancer-related gene combinations using a molecular e...

引用

7th IEEE International Conference on bioinformatics and Bioengineering, BIBE

作者： Park, Chan-Hoon Kim, Soo-Jin Kim, Sun Cho, Dong-Yeon Zhang, Byoung-Tak School of Computer Science and Engineering Seoul National University Seoul 151-742 Korea Republic of Graduate Program in Bioinformatics Seoul National University Seoul 151-742 Korea Republic of

ISBN: (纸本)1424415098

High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray analysis by managing large and complex data systematically. However, combinatorial interactions among genes have not been considered as a unit of the analysis since previous methods mainly focus on a whole gene or a single isolated gene. Here, we introduce a molecular evolutionary algorithm called probabilistic library model (PLM). In the PLM, library elements are generated from gene combinations. An evolutionary procedure is adopted to learn the probabilistic distribution of training samples. We apply the PLM to prostate cancer microarray data. The experimental results show that the PLM classifiers perform better than conventional methods such as neural networks and decision trees in accuracy. We also examine the evolved library to find cancer-related gene combinations. ©2007 IEEE.

关键词： Microarrays

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Study of equilibrium sense improvement displaying visual information

引用

Key Engineering Materials 2008年 381-382卷 369-372页

作者： Kim, G.B. Jeong, S.H. Chong, W.S. Kang, H.S. Kim, S.J. Kim, M.H. Hwang, J.W. Hong, C.U. Education Program for 21st Century Chonbuk National University Research Institute of Clinical Medicine Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of Department of Computer Engineering Graduate School Chonbuk National University Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of Department of Biomedical Engineering Graduate School Chonbuk National University Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of Department of Pharmacology College of Veterinary Medicine Chonbuk National University Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of Department of Bio and Applied Chemistry Iksan National College Ma-Dong Iksan Chonbuk 570-752 Korea Republic of Department of Thoracic and Cardiovascular Surgery Chonbuk National University Medical Schools Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of Collage of Engineering Chonbuk National University Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of Division of Bionics and Bioinformatics Collage of Engineering Chonbuk National University Duckjin-Dong Jeonju Chonbuk 561-756 Korea Republic of

The effectiveness of the visual feedback to improve ability with the sense and muscular strength of human in our bicycle system was quantitatively verified in our study. Experiments were performed to find the factors related to the training of equilibrium sense. The subjects consisted of young and the aged and the group of young people was compared against the group of the aged. We investigated three different training modes, non-visual feedback (NVF), visual feedback of the weight (VFW), and visual feedback of the center of pressure (VFC) and measured the riding time and speed, the weight shift, and the center of pressure (COP) for twenties and seventies. The results showed that the running capability of the young and the aged became much better after repeated training. In addition, it was found out that the ability to control postural balance and the capability of equilibrium sense were improved with the presentation of the visual feedback information. These results will be effective in the diagnosis of equilibrium sense and vestibular function with the aged.

关键词： Feedback

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Analysis of Protein Protein Dimeric Interfaces

Analysis of Protein Protein Dimeric Interfaces

引用

IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Feihong Wu Fadi Towfic Drena Dobbs Vasant Honavar Bioinformatics and Computational Biology Graduate Program Iowa State University Ames IA USA

We analyzed the structural properties and the local surface environment of surface amino acid residues of proteins using a large, non-redundant dataset of 2383 protein chains in dimeric complexes from PDB. We compared the interface residues and non-interface residues based on six properties: side chain orientation, surface roughness, solid angle, ex value, hydrophobicity and interface cluster size. The results of our analysis show that interface residues have side chains pointing inward; interfaces are rougher, tend to be flat, moderately convex or concave and protrude more relative to non-interface surface residues. Interface residues tend to be surrounded by hydrophobic neighbors and tend to form clusters consisting of three or more interfaces residues. These findings are consistent with previous published studies using much smaller datasets, while allowing for more qualitative conclusions due to our larger dataset. Preliminary results suggest the possibility of using the six the properties to identify putative interface residues.

关键词： Proteins Rough surfaces Surface roughness bioinformatics Amino acids Solids Sequences Biomedical computing Computer interfaces Biomedical measurements

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