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IEEE Symposium on bioinformatics and Bioengineering (BIBE)

作者： Theodoros G. Koutsandreas Eleftherios D. Pilalis Aristotelis A. Chatziioannou Metabolic Engineering and Bioinformatics Program Institute of Biology Athens Greece

The prediction of the putative enzymatic function of uncharacterized proteins is a major problem in the field of metagenomic research, where large amounts of sequences can be rapidly determined. In this work a machine-learning approach was developed, that attempts the prediction of enzymatic activity based on three protein domain databases, PFAM, CATH and SCOP, which contain functional and structural information of proteins as Hidden Markov Models. Separate and combined classifiers were trained by well-annotated data and their performance was assessed in order to compare the predictive power of different attribute sets corresponding to the three protein domain databases. All classifiers performed well, with an average accuracy of ~96% and an average AUC score of 0.84. As a conclusion, the classification procedure can be integrated to more extended metagenomic analysis workflows.

关键词： Proteins Hidden Markov models Training Databases Accuracy Biotechnology

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Prioritized functional analysis of biological experiments using resampling and noise control methodologies

Prioritized functional analysis of biological experiments us...

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IEEE Symposium on bioinformatics and Bioengineering (BIBE)

作者： Eleftherios D. Pilalis Aristotelis A. Chatziioannou Metabolic Engineering and Bioinformatics Program Institute of Biology Greece Athens

StRAnGER is a web application for the automated statistical analysis of annotated experiments, exploiting controlled biological vocabularies, like the Gene Ontology or the KEGG pathways terms. In the first version, StRAnGER featured various gene profiling platforms for functional analysis of genomic datasets, starting from a list of significant genes derived from statistical and empirical thresholds. In the current version, various major improvements have been implemented, namely a new ranking algorithm, the expansion of background distributions with protein annotations, the addition of a mode for batch experiments and a noise-control analysis that evaluates the robustness of the prioritized terms through iterative addition of random genes. Overall, StRAnGER enables a systems level functional interpretation through the utilization of bootstrapping techniques and the detection of distribution-independent term enrichments.

关键词： Finite element analysis Noise Proteins Ontologies Robustness Vocabulary

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Reconstruction of context-specific genome-scale metabolic models using multiomics data to study metabolic rewiring

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Current Opinion in Systems Biology 2019年 15卷 1-11页

作者： Cho, Jae Sung Gu, Changdai Han, Tae Hee Ryu, Jae Yong Lee, Sang Yup Metabolic and Biomolecular Engineering National Research Laboratory Department of Chemical and Biomolecular Engineering (BK21 Plus Program) Institute for the BioCentury Korea Advanced Institute of Science and Technology (KAIST) Daejeon South Korea Systems Metabolic Engineering and Systems Healthcare Cross-Generation Collaborative Laboratory KAIST Daejeon 34141 South Korea BioProcess Engineering Research Center KAIST Daejeon South Korea BioInformatics Research Center KAIST Daejeon South Korea

metabolic rewiring or reprogramming is the alteration of metabolism in living organisms, leading to disordered states aberrant from homeostasis. As large amounts of omics data become available, complex mechanisms leading to or driven by metabolic rewiring of cells can be better understood using reconstructed context-specific genome-scale metabolic models (GEMs). Here, we review recent advances in reconstructing context-specific GEMs for studying metabolic rewiring of human cells or tissues, from generic GEMs and omics databases to multiomics data integration methods. Also, we review recent studies that use context-specific GEMs to obtain insights such as identifying key regulators or therapeutic targets. Analyses of recent trends indicate the importance of integrating context-specific GEMs with multiscale networks for understanding metabolic diseases and advancing precision medicine. © 2019 Elsevier Ltd

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Current state and applications of microbial genome-scale metabolic models

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Current Opinion in Systems Biology 2017年 2卷 10-18页

作者： Kim, Won Jun Kim, Hyun Uk Lee, Sang Yup Metabolic and Biomolecular Engineering National Research Laboratory Department of Chemical and Biomolecular Engineering (BK21 Plus Program) Institute for the BioCentury Korea Advanced Institute of Science and Technology (KAIST) Daejeon 34141 South Korea BioInformatics Research Center KAIST Daejeon 34141 South Korea BioProcess Engineering Research Center KAIST Daejeon 34141 South Korea The Novo Nordisk Foundation Center for Biosustainability Technical University of Denmark Hørsholm Denmark

Genome-scale metabolic models (GEMs) are valuable in describing an organism's entire metabolism using genomic information and have made huge impact on systems biology and metabolic engineering. Here we review current state of microbial GEMs and their use in various applications. There has recently been much interest in reconstructing GEMs for microbial communities, reflecting the increasing importance of microbiome. Analyses of recent work suggest that the GEMs for the best studied microorganisms, new or less studied microorganisms, and also microbial communities need to be thoroughly validated with experimental data beyond simple gene essentiality and nutrient utilization capabilities. In this paper, computational modeling resources and frameworks developed recently for reconstructing GEMs of microorganisms and microbial communities together with their applications are reviewed. © 2017 Elsevier Ltd.

关键词： Genome-scale metabolic models (GEMs) metabolic modeling resources/frameworks Microbial community Microorganisms Model and non-model organisms

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Adaptive response to methylation damage in Escherichia colistudied by transcriptome and proteome analyses

Adaptive response to methylation damage in Escherichia colis...

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13th International Biotechnology Symposium and Exhibition(第13届IUPAC国际生物工程会议)

作者： Jong Hwan Baek Nam Su Heo Mee-Jung Han Sang Yup Lee Metabolic and Biomolecular Engineering National Research Laboratory Department of Chemical (&) Biomolecular Engineering (BK21 Program) BioPracess Engineering Research Center Center for Systems and Synthetic Biotechnology and Institute for the BioCentury Republic of Korea Metabolic and Biomolecular Engineering National Research Laboratory Department of Chemical (&) Biomolecular Engineering (BK21 Program) BioPracess Engineering Research Center Center for Systems and Synthetic Biotechnology and Institute for the BioCentury Republic of Korea Department of Bio and Brain Engineering and Bioinformatics Research Center KAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of Korea

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Comparative proteomic analysis of four biotechnologically important Escherichia coli strains for rational host strainselec tion

Comparative proteomic analysis of four biotechnologically im...

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13th International Biotechnology Symposium and Exhibition(第13届IUPAC国际生物工程会议)

作者： Xiao-Xia Xia Sang Yup Lee Department of Bio and Brain Engineering and Bioinformatics Research Center KAIST Daejeon Republic of Korea Metabolic and Biomolecular Engineering National Research Laboratory Department af Chemical and Biomolecular Engineering (BK21 Program) and BioProcess Engineering Research Center Center for Sys tems and Synthetic Biotechnology and Institute for the BioCenturyKAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of Korea Metabolic and Biomolecular Engineering National Research Laboratory Department af Chemical and Biomolecular Engineering (BK21 Program) and BioProcess Engineering Research Center Center for Sys tems and Synthetic Biotechnology and Institute for the BioCenturyKAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of Korea

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A software framework integrating gene expression patterns, binding site analysis and gene ontology to hypothesize gene regulation relationships

A software framework integrating gene expression patterns, b...

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IEEE International Conference on bioinformatics and Biomedicine (BIBM)

作者： Pujan Joshi Baikang Pei Seung-Hyun Hong Ivo Kalajzic Dong-Ju Shin David Rowe Dong-Guk Shin Computer Science and Engineering University of Connecticut Storrs CT Computational Biology and Bioinformatics Yale University New Haven CT Genetics & Dev. Biology University of Connecticut Health Center Farmington CT Metabolic Signaling and Disease Program Sanford-Burnham Medical Research Institute Orlando FL

One known challenge in analyzing gene expression data is to combine analysis outcomes obtained disparately by applying multiple, independent meta-analysis methods. Here we present an integrative computational system that narrows down biological hypotheses by integrating gene expression patterns, transcription factor (TF) binding site analysis outcomes, and Gene Ontology (GO) enrichment analysis outcomes. This system identifies regulated genes from microarray experiments through statistical processes, categorizes similarly behaving groups of genes and then carries out binding site analysis and gene function enrichment analysis based on some significant clusters. The output is an ordered set of "putative" pair-wise relationships between TFs and their potential target genes. The relationships are ranked based on their closeness to the experimental context. We demonstrate the effectiveness of our framework using two independent microarray data sets.

关键词： Gene expression Context Sociology Statistics bioinformatics Bones

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A systematic proteome-based approach for high-level extracellular production of recombinant proteins in Escherichia coli

A systematic proteome-based approach for high-level extracel...

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13th International Biotechnology Symposium and Exhibition(第13届IUPAC国际生物工程会议)

作者： Zhi-Gang Qian Xiao-Xia Xia Jong Hyun Choi Sang Yup Lee Department of Bio and Brain Engineering and Bioinformatics Research Center KAIST Daejeon Republic of Korea Metabolic and Biomolecular Engineering National Research Labora tory Department of Chemical and Biomolecular Engineering (BK21 Program) and BioProcess Engineering Research Center Center for Systems and Synthetic Biotechnology and Institute for the BioCenturyKAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of Korea Metabolic and Biomolecular Engineering National Research Labora tory Department of Chemical and Biomolecular Engineering (BK21 Program) and BioProcess Engineering Research Center Center for Systems and Synthetic Biotechnology and Institute for the BioCenturyKAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of Korea

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The extracellular proteomes of Escherichia coli B and K-12 strains and its application in the secretory production of recombinant proteins

The extracellular proteomes of Escherichia coli B and K-12 s...

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13th International Biotechnology Symposium and Exhibition(第13届IUPAC国际生物工程会议)

作者： Xiao-Xia Xia Zhi-Gang Qian Mee-Jung Han Sang Yup Lee Metabolic and Biomolecular Engineering National Research Lahoratory Department of Chemical and Biomolecular Engineering (BK21 Program) and BioProcess Engineering Research Center Cen terror Sys tems and Synthetic Biotechnology and Institute for the BioCenturyKAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of Korea Metabolic and Biomolecular Engineering National Research Lahoratory Department of Chemical and Biomolecular Engineering (BK21 Program) and BioProcess Engineering Research Center Cen terror Sys tems and Synthetic Biotechnology and Institute for the BioCenturyKAIST 335 Gwahangno Yuseong-gu Daejeon 305-701 Republic of KoreaDepartment of Bio and Brain Engineering and Bioinformatics Research Center KAIST Daejeon Republic of Korea

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Application of an integrative computational framework in trancriptomic data of atherosclerotic mice suggests numerous molecular players

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Advances in bioinformatics 2012年第1期2012卷 453513页

作者： Papadodima, Olga Sirsjö, Allan Kolisis, Fragiskos N. Chatziioannou, Aristotelis Metabolic Engineering and Bioinformatics Program Institute of Biological Research and Biotechnology National Hellenic Research Foundation 11635 Athens 48 Vas. Constantinou Avenue Greece Division of Clinical Medicine School of Health and Medical Sciences Örebro University Örebro SE-701 82 Sweden Biotechnology Laboratory School of Chemical Engineering National Technical University of Athens 15780 Athens Greece

Atherosclerosis is a multifactorial disease involving a lot of genes and proteins recruited throughout its manifestation. The present study aims to exploit bioinformatic tools in order to analyze microarray data of atherosclerotic aortic lesions of ApoE knockout mice, a model widely used in atherosclerosis research. In particular, a dynamic analysis was performed among young and aged animals, resulting in a list of 852 significantly altered genes. Pathway analysis indicated alterations in critical cellular processes related to cell communication and signal transduction, immune response, lipid transport, and metabolism. Cluster analysis partitioned the significantly differentiated genes in three major clusters of similar expression profile. Promoter analysis applied to functional related groups of the same cluster revealed shared putative cis-elements potentially contributing to a common regulatory mechanism. Finally, by reverse engineering the functional relevance of differentially expressed genes with specific cellular pathways, putative genes acting as hubs, were identified, linking functionally disparate cellular processes in the context of traditional molecular description. © 2012 Olga Papadodima et al.

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