Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7387955
Z. A. Marasigan, Abigaile Dionisio, Geoffrey A. Solano
Microarray is one of the technologies used in the interdisciplinary science of Biolnformatics. Its primary objective is to discover biological knowledge among genes through their expressions. Gene expressions usually come in large and multidimensional data which makes computational and statistical analyses necessary. Clustering of microarray data is one of these. Grouping similar genes together unfolds relationships of the biological properties of the genes under specific condition and, if supported by visualization, serves as good decision support for researchers. MaSOM is a software that uses Self-Organizing Maps, an Artificial Neural Network suitable both for clustering and for visualization. This tool can be used to analyze large data set by preprocessing, clustering, and visualizing two-color cDNA microarray data. It can therefore aid microarray researchers and practitioners in determining the initial properties of the data they study before proceeding to their actual experimentation onto their data.
{"title":"Microarray data clustering and visualization tool using self-organizing maps","authors":"Z. A. Marasigan, Abigaile Dionisio, Geoffrey A. Solano","doi":"10.1109/IISA.2015.7387955","DOIUrl":"https://doi.org/10.1109/IISA.2015.7387955","url":null,"abstract":"Microarray is one of the technologies used in the interdisciplinary science of Biolnformatics. Its primary objective is to discover biological knowledge among genes through their expressions. Gene expressions usually come in large and multidimensional data which makes computational and statistical analyses necessary. Clustering of microarray data is one of these. Grouping similar genes together unfolds relationships of the biological properties of the genes under specific condition and, if supported by visualization, serves as good decision support for researchers. MaSOM is a software that uses Self-Organizing Maps, an Artificial Neural Network suitable both for clustering and for visualization. This tool can be used to analyze large data set by preprocessing, clustering, and visualizing two-color cDNA microarray data. It can therefore aid microarray researchers and practitioners in determining the initial properties of the data they study before proceeding to their actual experimentation onto their data.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133917515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7388040
Athanasios Fevgas, Konstantis Daloukas, P. Tsompanopoulou, Panayiotis Bozanis
The solution of large-scale sparse linear systems arises in numerous scientific and engineering problems. Typical examples involve study of many real world multi-physics problems and the analysis of electric power systems. The latter involve key functions such as contingency, power flow and state estimation whose analysis amounts at solving linear systems with thousands or millions of equations. As a result, efficient and accurate solution of such systems is of paramount importance. The methods for solving sparse systems are distinguished in two categories, direct and iterative. Direct methods are robust but require large amounts of memory, as the size of the problem grows. On the other hand, iterative methods provide better performance but may exhibit numerical problems. In addition, continuous advances in computer hardware and computational infrastructures imposes new challenges and opportunities. GPUs, multi-core CPUs, late memory and storage technologies (flash and phase change memories) introduce new capabilities to optimizing sparse solvers. This work presents a comprehensive study of the performance of some, state of the art, sparse direct and iterative solvers on modern computer infrastructure and aims to identify the limits of each method on different computing platforms. We evaluated two direct solvers in different hardware configurations, examining their strengths and weaknesses both in main memory (in-core) and secondary memory (out-of-core) execution in a series of representative matrices from multi-physics and electric grid problems. Also, we provide a comparison with an iterative method, utilizing a general purpose preconditioner, implemented both on a GPU and a multi-core processor. Based on the evaluation results, we observe that direct solvers can be as efficient as their iterative counterparts if proper memory optimizations are applied. In addition, we demonstrate that GPUs can be utilized as efficient computational platforms for tackling the analysis of electric power systems.
{"title":"Efficient solution of large sparse linear systems in modern hardware","authors":"Athanasios Fevgas, Konstantis Daloukas, P. Tsompanopoulou, Panayiotis Bozanis","doi":"10.1109/IISA.2015.7388040","DOIUrl":"https://doi.org/10.1109/IISA.2015.7388040","url":null,"abstract":"The solution of large-scale sparse linear systems arises in numerous scientific and engineering problems. Typical examples involve study of many real world multi-physics problems and the analysis of electric power systems. The latter involve key functions such as contingency, power flow and state estimation whose analysis amounts at solving linear systems with thousands or millions of equations. As a result, efficient and accurate solution of such systems is of paramount importance. The methods for solving sparse systems are distinguished in two categories, direct and iterative. Direct methods are robust but require large amounts of memory, as the size of the problem grows. On the other hand, iterative methods provide better performance but may exhibit numerical problems. In addition, continuous advances in computer hardware and computational infrastructures imposes new challenges and opportunities. GPUs, multi-core CPUs, late memory and storage technologies (flash and phase change memories) introduce new capabilities to optimizing sparse solvers. This work presents a comprehensive study of the performance of some, state of the art, sparse direct and iterative solvers on modern computer infrastructure and aims to identify the limits of each method on different computing platforms. We evaluated two direct solvers in different hardware configurations, examining their strengths and weaknesses both in main memory (in-core) and secondary memory (out-of-core) execution in a series of representative matrices from multi-physics and electric grid problems. Also, we provide a comparison with an iterative method, utilizing a general purpose preconditioner, implemented both on a GPU and a multi-core processor. Based on the evaluation results, we observe that direct solvers can be as efficient as their iterative counterparts if proper memory optimizations are applied. In addition, we demonstrate that GPUs can be utilized as efficient computational platforms for tackling the analysis of electric power systems.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"329 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134159767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7387988
Touqeer Ahmad, G. Bebis, M. Nicolescu, A. Nefian, T. Fong
Horizon line detection requires finding a boundary which segments an image into sky and non-sky regions. It has many applications including visual geo-localization and geo-tagging, robot navigation/localization, and ship detection and port security. Recently, two machine learning based approaches have been proposed for horizon line detection: one relying on edge classification and the other relying on pixel classification. In the edge-based approach, a classifier is used to refine the edge map by removing non-horizon edges. The refined edge map is then used to form a multi-stage graph where dynamic programming is applied to extract the horizon line. In the edge-less approach, classification is used to obtain a confidence of horizon-ness at each pixel location. The horizon line is then extracted by applying dynamic programming on the resultant dense classification map rather than on the edge map. Both approaches have shown to outperform the classical approach where dynamic programming is applied on the non-refined edge map. In this paper, we provide a comparison between the edge-less and edge-based approaches using two challenging data sets. Moreover, we propose fusing the information about the horizon-ness and edge-ness of each pixel. Our experimental results illustrate that the proposed fusion approach outperforms both the edge-based and edge-less approaches.
{"title":"Fusion of edge-less and edge-based approaches for horizon line detection","authors":"Touqeer Ahmad, G. Bebis, M. Nicolescu, A. Nefian, T. Fong","doi":"10.1109/IISA.2015.7387988","DOIUrl":"https://doi.org/10.1109/IISA.2015.7387988","url":null,"abstract":"Horizon line detection requires finding a boundary which segments an image into sky and non-sky regions. It has many applications including visual geo-localization and geo-tagging, robot navigation/localization, and ship detection and port security. Recently, two machine learning based approaches have been proposed for horizon line detection: one relying on edge classification and the other relying on pixel classification. In the edge-based approach, a classifier is used to refine the edge map by removing non-horizon edges. The refined edge map is then used to form a multi-stage graph where dynamic programming is applied to extract the horizon line. In the edge-less approach, classification is used to obtain a confidence of horizon-ness at each pixel location. The horizon line is then extracted by applying dynamic programming on the resultant dense classification map rather than on the edge map. Both approaches have shown to outperform the classical approach where dynamic programming is applied on the non-refined edge map. In this paper, we provide a comparison between the edge-less and edge-based approaches using two challenging data sets. Moreover, we propose fusing the information about the horizon-ness and edge-ness of each pixel. Our experimental results illustrate that the proposed fusion approach outperforms both the edge-based and edge-less approaches.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132811149","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7388052
Aphrodite Veneti, C. Konstantopoulos, G. Pantziou
The paper presents a real time weather routing solution based on an Evolutionary Algorithm (EA). The objectives to be minimized are the mean total risk and fuel cost, where the route of a ship is optimized while taking into consideration the time-varying sea and weather conditions and there is also a constraint on the total passage time of the route. Safety is also taken into account by applying restrictions following the guidelines of the International Maritime Organization (IMO). The proposed EA implementation is tested on real life instances and compared with an exact algorithm.
{"title":"An evolutionary approach to multi-objective ship weather routing","authors":"Aphrodite Veneti, C. Konstantopoulos, G. Pantziou","doi":"10.1109/IISA.2015.7388052","DOIUrl":"https://doi.org/10.1109/IISA.2015.7388052","url":null,"abstract":"The paper presents a real time weather routing solution based on an Evolutionary Algorithm (EA). The objectives to be minimized are the mean total risk and fuel cost, where the route of a ship is optimized while taking into consideration the time-varying sea and weather conditions and there is also a constraint on the total passage time of the route. Safety is also taken into account by applying restrictions following the guidelines of the International Maritime Organization (IMO). The proposed EA implementation is tested on real life instances and compared with an exact algorithm.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131177087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7388080
M. Brignone, F. Delfino, F. Pampararo, R. Procopio, M. Rossi, L. Barillari
In this contribution the possible benefits of the integration of a storage system (ST) and a photovoltaic power plant (PV) are investigated by means of a Heuristic Rules System (HRS), used both for the determination of the optimal size of the components and for the power production scheduling. The HRS takes into account the well-known electrical constraints and aims at satisfying the electrical demand following a priority order (PV, ST, main grid). Experimental results in the case of four possible scenarios are presented and discussed.
{"title":"Energy management in hybrid systems coupling PV and electrical storage","authors":"M. Brignone, F. Delfino, F. Pampararo, R. Procopio, M. Rossi, L. Barillari","doi":"10.1109/IISA.2015.7388080","DOIUrl":"https://doi.org/10.1109/IISA.2015.7388080","url":null,"abstract":"In this contribution the possible benefits of the integration of a storage system (ST) and a photovoltaic power plant (PV) are investigated by means of a Heuristic Rules System (HRS), used both for the determination of the optimal size of the components and for the power production scheduling. The HRS takes into account the well-known electrical constraints and aims at satisfying the electrical demand following a priority order (PV, ST, main grid). Experimental results in the case of four possible scenarios are presented and discussed.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133581482","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7387979
Eirini Takoulidou, K. Chorianopoulos
The need for more experimental data, but also quicker and cheaper, lead us beyond traditional lab experiments, approaching a new subject pool via a crowdsourcing platform. SocialSkip is an open system that leverages the video clickstream data for extracting useful information about the video content and the viewers. The difficulty of embedding a pre-existing system as a task demands a carefully designed interface, adjusting experiments and be aware of workers' cheating behavior. We present a replicable task design and by analyzing crowdsourced results, we highlight problems in experimental procedure and propose potential solutions for future crowdsourcing experiments. The proposed crowdsourcing methodology achieved the collection of a significant amount of video clickstream data, in a timely manner and with affordable cost. Our findings indicate that future social media analytics systems should include an integrated crowdsourcing module. Further research should focus on collecting more data by controlling the random worker behavior a priori.
{"title":"Crowdsourcing experiments with a video analytics system","authors":"Eirini Takoulidou, K. Chorianopoulos","doi":"10.1109/IISA.2015.7387979","DOIUrl":"https://doi.org/10.1109/IISA.2015.7387979","url":null,"abstract":"The need for more experimental data, but also quicker and cheaper, lead us beyond traditional lab experiments, approaching a new subject pool via a crowdsourcing platform. SocialSkip is an open system that leverages the video clickstream data for extracting useful information about the video content and the viewers. The difficulty of embedding a pre-existing system as a task demands a carefully designed interface, adjusting experiments and be aware of workers' cheating behavior. We present a replicable task design and by analyzing crowdsourced results, we highlight problems in experimental procedure and propose potential solutions for future crowdsourcing experiments. The proposed crowdsourcing methodology achieved the collection of a significant amount of video clickstream data, in a timely manner and with affordable cost. Our findings indicate that future social media analytics systems should include an integrated crowdsourcing module. Further research should focus on collecting more data by controlling the random worker behavior a priori.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114850757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7387958
Vangelis Marinakis, Alexandra Papadopoulou, G. Anastasopoulos, H. Doukas, J. Psarras
In recent years, the European Union (EU) has developed a shared European vision of sustainable urban development. Towards this direction, holistic solutions and advanced energy management services are necessary, addressed to any local authority that has as purpose to implement sustainable energy action plans. In this context, the aim of this paper is to present an advanced Information and Communication Technologies (ICT) platform for real-time monitoring and infrastructure efficiency at the city level, namely a Web Portal addressed to city authorities. The Web Portal will enable the city administration to collect data for energy management, real-time monitoring and billing purposes from city's infrastructure, sensors, meters and other energy sources and react to critical incidents or systems failure in an urban (city) environment. All the collected data will be handled by the "green" tools of the ICT platform, focused on the city's municipal buildings, pillars/poles and electric vehicle stations.
{"title":"Advanced ICT platform for real-time monitoring and infrastructure efficiency at the city level","authors":"Vangelis Marinakis, Alexandra Papadopoulou, G. Anastasopoulos, H. Doukas, J. Psarras","doi":"10.1109/IISA.2015.7387958","DOIUrl":"https://doi.org/10.1109/IISA.2015.7387958","url":null,"abstract":"In recent years, the European Union (EU) has developed a shared European vision of sustainable urban development. Towards this direction, holistic solutions and advanced energy management services are necessary, addressed to any local authority that has as purpose to implement sustainable energy action plans. In this context, the aim of this paper is to present an advanced Information and Communication Technologies (ICT) platform for real-time monitoring and infrastructure efficiency at the city level, namely a Web Portal addressed to city authorities. The Web Portal will enable the city administration to collect data for energy management, real-time monitoring and billing purposes from city's infrastructure, sensors, meters and other energy sources and react to critical incidents or systems failure in an urban (city) environment. All the collected data will be handled by the \"green\" tools of the ICT platform, focused on the city's municipal buildings, pillars/poles and electric vehicle stations.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"187 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115113006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7388072
Georgios M. Santipantakis, Konstantinos I. Kotis, G. Vouros
Recent environmental disasters in the sea, have highlighted the need for efficient maritime surveillance. Currently, maritime navigation technology automatically provides real time data from vessels, that together with other historical data can be processed in an integrated way to detect complex events and support decision making. Ontology-Based Data Access (OBDA) frameworks can be employed to access data towards this effort. Integration of data is critical, but the heterogeneity and the large amount of data make this a difficult task. In this paper we present two systems that we have implemented using different OBDA frameworks, emphasizing on the semantic integration of data from disparate sources to support complex event recognition. We discuss the features of each system separately and the lessons learned from this effort.
{"title":"Ontology-based data sources' integration for maritime event recognition","authors":"Georgios M. Santipantakis, Konstantinos I. Kotis, G. Vouros","doi":"10.1109/IISA.2015.7388072","DOIUrl":"https://doi.org/10.1109/IISA.2015.7388072","url":null,"abstract":"Recent environmental disasters in the sea, have highlighted the need for efficient maritime surveillance. Currently, maritime navigation technology automatically provides real time data from vessels, that together with other historical data can be processed in an integrated way to detect complex events and support decision making. Ontology-Based Data Access (OBDA) frameworks can be employed to access data towards this effort. Integration of data is critical, but the heterogeneity and the large amount of data make this a difficult task. In this paper we present two systems that we have implemented using different OBDA frameworks, emphasizing on the semantic integration of data from disparate sources to support complex event recognition. We discuss the features of each system separately and the lessons learned from this effort.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121916171","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7388089
S. Muuraiskangas, J. Merilahti, Milla Immonen, A. Hedman, J. Hallberg
Dementia has become a prevalent problem with our aging population. Dementia is threat to our independence because our independence relies on our cognitive performance. Cognitive performance declines as the years advance but it can and should be nurtured to keep it at sufficient functional level. Even though mobile technology has potential to be the desired low-cost and effective means to healthy living, it requires the driving force, motivation, to actually get the person to the destination. In this paper we present a motivational strategy for mHealth (mobile health) application for cognitive endurance.
{"title":"Motivational strategy for a cognitive endurance mHealth application","authors":"S. Muuraiskangas, J. Merilahti, Milla Immonen, A. Hedman, J. Hallberg","doi":"10.1109/IISA.2015.7388089","DOIUrl":"https://doi.org/10.1109/IISA.2015.7388089","url":null,"abstract":"Dementia has become a prevalent problem with our aging population. Dementia is threat to our independence because our independence relies on our cognitive performance. Cognitive performance declines as the years advance but it can and should be nurtured to keep it at sufficient functional level. Even though mobile technology has potential to be the desired low-cost and effective means to healthy living, it requires the driving force, motivation, to actually get the person to the destination. In this paper we present a motivational strategy for mHealth (mobile health) application for cognitive endurance.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129440218","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2015-07-06DOI: 10.1109/IISA.2015.7388007
Lejun Christian L. Osorio, M. Carillo, Geoffrey A. Solano, H. Adorna
Phenograms have already been used many years back to depict taxonomic relationships among organisms based on overall similarity among a variety of characteristics available at the time. These recent years, however, have brought phenomenal advances in experimental techniques in biological research. These have resulted in large amounts of biological network data being unearthed. Among these are metabolic networks. Analyzing the network topology of these metabolic networks across taxa can uncover important biological information that is independent of other currently available biological information. This study explores topological similarities between the glycolysis and citrate cycle metabolic networks of different taxa to build phenograms. A novel approach of generating phenograms using Jaccard Similary Indices and Hamming Distances of the graphs bit codes are presented. The resulting phenograms are compared with those generated by NCBI gene sequences using Phyllp branch matchings and maximum consensus trees.
{"title":"Generating phenograms using frequent structure mining over metabolic pathways","authors":"Lejun Christian L. Osorio, M. Carillo, Geoffrey A. Solano, H. Adorna","doi":"10.1109/IISA.2015.7388007","DOIUrl":"https://doi.org/10.1109/IISA.2015.7388007","url":null,"abstract":"Phenograms have already been used many years back to depict taxonomic relationships among organisms based on overall similarity among a variety of characteristics available at the time. These recent years, however, have brought phenomenal advances in experimental techniques in biological research. These have resulted in large amounts of biological network data being unearthed. Among these are metabolic networks. Analyzing the network topology of these metabolic networks across taxa can uncover important biological information that is independent of other currently available biological information. This study explores topological similarities between the glycolysis and citrate cycle metabolic networks of different taxa to build phenograms. A novel approach of generating phenograms using Jaccard Similary Indices and Hamming Distances of the graphs bit codes are presented. The resulting phenograms are compared with those generated by NCBI gene sequences using Phyllp branch matchings and maximum consensus trees.","PeriodicalId":433872,"journal":{"name":"2015 6th International Conference on Information, Intelligence, Systems and Applications (IISA)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129474350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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