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Joint 8th International Conference on Soft Computing and Intelligent Systems (SCIS) / 17th International Symposium on Advanced Intelligent Systems (ISIS)

作者： Horiguchi, Yukio Suzuki, Takaya Sawaragi, Tetsuo Nakanishi, Hiroaki Takimoto, Tomoharu Kyoto Univ Dept Mech Engn & Sci Kyoto Japan Kyoto Univ Grad Sch Informat Kyoto Japan West Japan Railway Co Safety Res Inst Osaka Japan

ISBN: (纸本)9781509026784

In the present study, dominant eye-gaze patterns in professional train drivers' visual behavior are investigated using the markov cluster (MCL) algorithm. Applying the MCL algorithm results in a common gaze pattern showing a sort of perception tactic the drivers usually follow. The drivers repetitively move their gaze ahead soon after looking at somewhere else, independently of their years of experience. They are, however, found different in that experienced drivers can consistently follow the tactic while inexperienced drivers cannot. Time variation in the number of attentive pattern deviations demonstrates that, as well as the inexperienced drivers made higher frequency and larger fluctuations of pattern deviation, there were several particular segments in the route in which intensive pattern deviations arose in common. Inexperienced drivers would make intensive pattern deviations in such route segments that may have higher requirements of their cognitive resources.

关键词： eye-gaze analysis markov cluster algorithm pattern extraction train driving visual perceptual skills

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Graph analysis and clustering of proteins linked with COVID-19

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INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2022年第1期16卷 145-158页

作者： Susymary, J. Deepalakshmi, P. Kalasalingam Acad Res & Educ Dept Comp Applicat Krishnankoil 626126 Tamil Nadu India Kalasalingam Acad Res & Educ Dept Comp Sci & Engn Krishnankoil Tamil Nadu India

A remarkable number of scientific initiatives are in practice to encounter the new coronavirus epidemic (COVID-19). One of the biggest challenges faced by the COVID-19 researchers in the therapeutic field is the knowledge about the biological functions in disease-human interacting proteins. The detection of COVID-19 protein complexes, a group of proteins that possess the same biological functions, helps in better understanding of the biological processes in our body. The main contribution of this work is to cluster proteins that perform the same biological functions to increase the knowledge about the COVID-19 disease-human interacting proteins. The authors investigated proteins linked with COVID-19 disease by creating a disease-human protein-protein interaction graph. Topological means of graph analysis and graph clustering have been employed to group proteins that possess the same biological functions. These clusters will be the protein complexes that work together to carry out a specific biological function in a human cell. Moreover, through the cluster analysis, we can uncover previously unknown COVID-19 disease-human protein links that are beneficial for promising knowledge discovery. Also, the authors evaluated how the markov cluster algorithm, a graph-based algorithm finds interesting patterns of similar features from COVID-19 disease-human protein-protein interaction graph. The markov cluster algorithm results in six statistically significant protein clusters, including cluster (A): keratinization (3.50E-71), (B): regulation of cellular process (6.62E-05), (C): regulation of cell cycle (1.31E-27), (D): mitotic cell cycle (1.66E-06), (E): regulation of phosphoprotein phosphatase activity (1.15E-09), and (G): G2/M transition of mitotic cell cycle (3.03E-07).

关键词： COVID-19 protein-protein interaction graph clustering markov cluster algorithm protein clusters

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A Novel Way of Comparing Protein 3D Structure Using Graph Partitioning Approach

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IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2021年第4期18卷 1361-1368页

作者： Angadi, Ulavappa B. Chaturvedi, Krishna Kumar Srivastava, Sudhir Rai, Anil ICAR Indian Agr Stat Res Inst Ctr Agr Bioinformat New Delhi India

Alignment and comparison of protein 3D structures is an important and fundamental task in structural biology to study evolutionary, functional and structural relatedness among proteins. Since two decades, the research on protein structure alignment has been taken up on priority and numbers of research articles are being published. There are incremental advances over previous efforts, and still these methods continue to improve over the time and still this is an open problem in structural biology. A novel methodology has been developed for comparing protein 3D structure by employing conversion of pair of protein 3D structures into 2D graphs (undirected weighted graph), partitioning of 2D graphs into sub-graphs, matching sub-graphs with main graphs and finally these sub-graphs matches calculates similarity between the pair of proteins. The proposed method has been implemented in MATLAB and R Package. The performance of the developed methodology is tested with four existing best methods such as CE, jFATCAT, TM_Align and Dali on 100 proteins benchmark dataset with SCOP database. The proposed method is efficient in terms of time complexity, accuracy, grouping of proteins in relevant structural groups and provides additional information towards non-bonded interactions and sub-graphs indicates the dominance of secondary structure.

关键词： Proteins Three-dimensional displays Two dimensional displays Solid modeling clustering algorithms Topology Protein 3D structure alignment graph partitioning markov cluster algorithm protein structure comparison

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ProMoCell and ProModb: Web services for analyzing interaction-based functionally localized protein modules in a cell

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JOURNAL OF MOLECULAR MODELING 2022年第6期28卷 167-167页

作者： Das, Barnali Mitra, Pralay Indian Inst Technol Dept Comp Sci & Engn Kharagpur 721302 W Bengal India

The modular organization of a cell which can be determined by its interaction network allows us to understand a mesh of cooperation among the functional modules. Therefore, cellular-level identification of functional modules aids in understanding the functional and structural characteristics of the biological network of a cell and also assists in determining or comprehending the evolutionary signal. We develop ProMoCell that performs real-time Web scraping for generating clusters of the cellular level functional units of an organism. ProMoCell constructs the Protein Locality Graphs and clusters the cellular level functional units of an organism by utilizing experimentally verified data from various online sources. Also, we develop ProModb, a database service that houses precomputed whole-cell protein-protein interaction network-based functional modules of an organism using ProMoCell. Our Web service is entirely synchronized with the KEGG pathway database and allows users to generate spatially localized protein modules for any organism belonging to the KEGG genome using its real-time Web scraping characteristics. Hence, the server will host as many organisms as is maintained by the KEGG database. Our Web services provide the users a comprehensive and integrated tool for an efficient browsing and extraction of the spatial locality-based protein locality graph and the functional modules constructed by gathering experimental data from several interaction databases and pathway maps. We believe that our Web services will be beneficial in pharmacological research, where a novel research domain called modular pharmacology has initiated the study on the diagnosis, prevention, and treatment of deadly diseases using functional modules.

关键词： Spatial localization Functional modules Protein interaction networks Protein locality graph markov cluster algorithm

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Eco-modular product architecture identification and assessment for product recovery

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JOURNAL OF INTELLIGENT MANUFACTURING 2019年第1期30卷 383-403页

作者： Kim, Samyeon Moon, Seung Ki Nanyang Technol Univ Sch Mech & Aerosp Engn 50 Nanyang Ave Singapore 639798 Singapore

In order to improve the efficiency of disassembly and product recovery of an abandoned product at the end-of-life stage, it is essential to develop modular product architecture by considering manufacturing and recovering processes in early product design stage. In this paper, a novel concept of a design methodology is introduced to develop eco-modular product architecture and assess the modularity of the architecture from the viewpoint of product recovery. Eco-modular product architecture contributes to enhancing product recovery processes by recycling and reusing modules without full disassembly at component or material levels. It leads to less consumption of natural resources and less landfill damage to the environment. Three sustainable modular drivers, namely, interface complexity, material similarity, and lifespan similarity, are introduced to reconstruct the modular architecture of commercial products into the eco-modular architecture. Alternatives of modular architectures are identified by markov cluster algorithm based on these sustainable modular drivers and physical interconnections of the components of product architecture. To select the eco-modular architecture from these alternatives, we propose modularity assessment metrics to identify independent interactions between modules and the degrees of similarity within each module. To demonstrate the effectiveness of the proposed methodology, a case study is performed with a coffee maker.

关键词： Eco-module markov cluster algorithm Modularity assessment Product architecture Product recovery

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Identification of gene co-expression networks involved in cold resistance of Lilium lancifolium

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BIOLOGIA PLANTARUM 2018年第2期62卷 287-298页

作者： Yong, Y. B. Li, W. Q. Wang, J. M. Zhang, Y. Lu, Y. M. Beijing Forestry Univ Coll Landscape Architecture China Natl Engn Res Ctr Floriculture Beijing Key Lab Ornamental Germplasm Innovat & Mo Beijing 100083 Peoples R China

Low temperature can affect the growth and development of lily, limiting the application of commercial cultivars in outdoor. Lilium lancifolium is an important cold-resistant wild lily, but little is known about how L. lancifolium tolerates cold stress at the molecular level. In this study, we identified and characterized genes and transcription factors associated with cold stress in control plants and plants treated by 4A degrees C for 1 - 24 h. The construction of a highest reciprocal rank-based gene co-expression network along with its partition into defined functional modules using markov cluster algorithm resulted in identification of 30 gene modules and some of them were significantly enriched with various kinds of stress response under 4A degrees C. These gene modules were associated with metabolic processes, cellular processes, regulation of biological processes, establishment of localization, and responses to stimuli. Moreover, three transcription factors that may regulate the downstream genes involved in response to stimuli were also found. We further studied the expression pattern and tissue specificity of these transcription factors. The functional evaluation of the various interesting genes in this study will probably provide novel discovery of pathway members and regulators associated with cold resistance in lily.

关键词： differentially expressed genes markov cluster algorithm transcription factors

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Extracting Train Driver's Eye-Gaze Patterns Using Graph clustering

Extracting Train Driver's Eye-Gaze Patterns Using Graph Clus...

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13th IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design, and Evaluation of Human-Machine Systems (HMS)

作者： Horiguchi, Yukio Suzuki, Takaya Sawaragi, Tetsuo Nakanishi, Hiroaki Takimoto, Tomoharu Kyoto Univ Dept Mech Engn & Sci Kyoto 6158540 Japan Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan West Japan Railway Co Safety Res Inst Osaka 5450053 Japan

The present paper investigates train drivers' eye-gaze data to find important features to explain behavioral differences between experienced and inexperienced drivers. The obtained eye-gaze data. contain too complex transition structure to find any meaningful patterns that might be common across or differentiate. drivers. The markov cluster algorithm, which is an unsupervised algorithm for graph clustering, is therefore utilized to divide such a structure into clusters that represent constituent eye-gaze patterns of frequent occurrence. As a result, a common eye-gaze pattern was identified to represent a perception tactic that drivers would repetitively move their gaze ahead soon after looking at other specific areas. Comparing cluster Structures extracted with different clustering parameter settings clarified that all of the drivers implement this tactic more or less, but that they arc different in that the experienced drivers can consistently follow it while the inexperienced drivers can not. (C) 2016, IFAC (International Federation Control) Hosting By Elsevier Ltd. All rights reserverd.

关键词： eye-gaze analysis markov cluster algorithm patternextraction visual perceptual skills train driving

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Link community detection based on line graphs with a novel link similarity measure

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INTERNATIONAL JOURNAL OF MODERN PHYSICS B 2016年第6期30卷 1650023-1650023页

作者： Wang, Guishen Huang, Lan Wang, Yan Pang, Wei Ma, Qin Jilin Univ Coll Comp Sci & Technol Changchun 130012 Peoples R China Jilin Univ Minist Educ Key Lab Symbol Computat & Knowledge Engn Changchun 130012 Peoples R China Univ Aberdeen Sch Nat & Comp Sci Aberdeen AB24 3UE Scotland S Dakota State Univ Dept Plant Sci Brookings SD 57007 USA

Link community gradually unfolds its capacity in complex network research. In this paper, a novel link similarity measure on line graphs is proposed. This measure can be adapted to different types of networks with an adjustable parameter. We prove its value converges to a limit on line graphs with the relationship of the nonneighbor links taken into account. Based on this similarity measure, we propose a novel link community detection algorithm for link clustering on line graphs. The detection algorithm combines the novel link similarity measure with the classic markov cluster (MCL) algorithm and determines the link community partitions by calculating an extended modularity measure. Extensive experiments on two types of complex networks demonstrate the effectiveness, reliability and rationality of our solution in contrast to the other two classical algorithms.

关键词： Link community detection markov cluster algorithm line graphs overlapping community detection link similarity complex networks

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Endogenous murine leukemia retroviral variation across wild European and inbred strains of house mouse

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BMC GENOMICS 2015年第1期16卷 1-13页

作者： Hartmann, Stefanie Hasenkamp, Natascha Mayer, Jens Michaux, Johan Morand, Serge Mazzoni, Camila J. Roca, Alfred L. Greenwood, Alex D. Univ Potsdam Inst Biochem & Biol D-14476 Potsdam Germany Max Planck Inst Evolutionary Biol Dept Evolutionary Genet D-24306 Plon Germany Univ Saarland Fac Med Dept Human Genet Ctr Human & Mol Biol D-66421 Homburg Germany Ctr Biol & Gest Populat F-34988 Montferrier Le Lez France Univ Liege Conservat Genet Unit Inst Bot B22 B-4000 Liege Belgium CIRAD F-34398 Montpellier 5 France Berlin Ctr Genom Biodivers Res D-14195 Berlin Germany Leibniz Inst Zoo & Wildlife Res D-10315 Berlin Germany Univ Illinois Dept Anim Sci Urbana IL 61801 USA

Background: Endogenous murine leukemia retroviruses (MLVs) are high copy number proviral elements difficult to comprehensively characterize using standard low throughput sequencing approaches. However, high throughput approaches generate data that is challenging to process, interpret and present. Results: Next generation sequencing (NGS) data was generated for MLVs from two wild caught Mus musculus domesticus (from mainland France and Corsica) and for inbred laboratory mouse strains C3H, LP/J and SJL. Sequence reads were grouped using a novel sequence clustering approach as applied to retroviral sequences. A markov cluster algorithm was employed, and the sequence reads were queried for matches to specific xenotropic (Xmv), polytropic (Pmv) and modified polytropic (Mpmv) viral reference sequences. Conclusions: Various MLV subtypes were more widespread than expected among the mice, which may be due to the higher coverage of NGS, or to the presence of similar sequence across many different proviral loci. The results did not correlate with variation in the major MLV receptor Xpr1, which can restrict exogenous MLVs, suggesting that endogenous MLV distribution may reflect gene flow more than past resistance to infection.

关键词： Murine leukemia virus Endogenous retrovirus Xpr1 XMRV Genomic evolution markov cluster algorithm

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Data Mining Driven Visual Pattern Discovery RBEI-IYER-MC2

Data Mining Driven Visual Pattern Discovery RBEI-IYER-MC2

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IEEE Conference Visual Analytics Sci Technology

作者： Singhal, Manik Lekkala, Prakash Shivashankar, M. R. Iyer, Parameshwaran S. Robert Bosch Engn & Business Solut Ltd PJ DM G1 Bangalore Karnataka India

ISBN: (纸本)9781479962273

In the following work we present a short description of data mining methods & techniques we apply to create a visual framework for VAST Mini Challenge 2 (VAST-MC2). We provide a brief description of the problem, followed by our approach to arriving on a visual framework. From our framework, post visual mining for patterns;we list some of our key findings.

关键词： Spatial Temporal clustering markov cluster algorithm Event-Information Framework Ripley-L factor

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