{"title":"Evolutionary Models","authors":"D. Liberles, B. Holland","doi":"10.1201/b11422-23","DOIUrl":"https://doi.org/10.1201/b11422-23","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121856392","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 : 2018-10-04DOI: 10.1016/B978-0-12-809633-8.20327-0
A. Garro, M. Mühlhäuser, A. Tundis, S. Mariani, Andrea Omicini, Giuseppe Vizzari
{"title":"Intelligent Agents and Environment","authors":"A. Garro, M. Mühlhäuser, A. Tundis, S. Mariani, Andrea Omicini, Giuseppe Vizzari","doi":"10.1016/B978-0-12-809633-8.20327-0","DOIUrl":"https://doi.org/10.1016/B978-0-12-809633-8.20327-0","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123776888","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 : 2018-10-04DOI: 10.1016/B978-0-12-809633-8.20328-2
A. Garro, M. Mühlhäuser, A. Tundis, M. Baldoni, C. Baroglio, F. Bergenti, Paolo Torroni
{"title":"Intelligent Agents: Multi-Agent Systems","authors":"A. Garro, M. Mühlhäuser, A. Tundis, M. Baldoni, C. Baroglio, F. Bergenti, Paolo Torroni","doi":"10.1016/B978-0-12-809633-8.20328-2","DOIUrl":"https://doi.org/10.1016/B978-0-12-809633-8.20328-2","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123241527","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 : 2018-09-06DOI: 10.1016/b978-0-12-809633-8.20442-1
E. Ramlan, M. F. Raih
{"title":"Engineering of Supramolecular RNA Structures","authors":"E. Ramlan, M. F. Raih","doi":"10.1016/b978-0-12-809633-8.20442-1","DOIUrl":"https://doi.org/10.1016/b978-0-12-809633-8.20442-1","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124994429","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 : 2018-09-06DOI: 10.1016/b978-0-12-809633-8.20355-5
Haiying Wang, Jyotsna Talreja Wassan, Huiru Zheng
{"title":"Measurements of Accuracy in Biostatistics","authors":"Haiying Wang, Jyotsna Talreja Wassan, Huiru Zheng","doi":"10.1016/b978-0-12-809633-8.20355-5","DOIUrl":"https://doi.org/10.1016/b978-0-12-809633-8.20355-5","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117189105","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 : 2018-09-06DOI: 10.1016/B978-0-12-809633-8.20100-3
L. Chong, Asif M. Khan
{"title":"Vaccine Target Discovery","authors":"L. Chong, Asif M. Khan","doi":"10.1016/B978-0-12-809633-8.20100-3","DOIUrl":"https://doi.org/10.1016/B978-0-12-809633-8.20100-3","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124824717","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 : 2015-10-15DOI: 10.1002/9780470015902.A0003033.PUB3
N. Dawson, Sayoni Das, J. Lees, C. Orengo
To understand and map the universe of protein structures, it is necessary to collate, annotate and classify these structures in a rational scheme. While the individual protein structures reveal much about the specific molecular mechanisms that underlie a particular biological function, taken together this body of data also allows biologists to explore the evolution of structure and function. As structure is much better conserved than sequence, these data also facilitate the recognition of evolutionary relationships that are hidden at the sequence level. The different approaches that have been taken to tackle this problem include the identification of protein domains, phylogenetic and phenetic classification and hierarchical and nearest-neighbour clustering. Powerful sequence searching methods then enable structural assignments to be allocated to genomic data. Key Concepts Proteins comprise recognisable smaller sequence domains. Domains usually consist of secondary and supersecondary structures and have an average size of 150 ± 50 residues. These domains may be thought of as units of evolution, which recur in many proteins in various combinations. Structural classifications have been developed that group domains into fold and sequence families. The phenetic approach groups the proteins according to their structural characteristics. The phylogenetic approach groups proteins into families according to their evolutionary history. Keywords: protein structure classification; common folds; protein architecture; structural comparison; genomes
{"title":"Protein Structure Classification","authors":"N. Dawson, Sayoni Das, J. Lees, C. Orengo","doi":"10.1002/9780470015902.A0003033.PUB3","DOIUrl":"https://doi.org/10.1002/9780470015902.A0003033.PUB3","url":null,"abstract":"To understand and map the universe of protein structures, it is necessary to collate, annotate and classify these structures in a rational scheme. While the individual protein structures reveal much about the specific molecular mechanisms that underlie a particular biological function, taken together this body of data also allows biologists to explore the evolution of structure and function. As structure is much better conserved than sequence, these data also facilitate the recognition of evolutionary relationships that are hidden at the sequence level. The different approaches that have been taken to tackle this problem include the identification of protein domains, phylogenetic and phenetic classification and hierarchical and nearest-neighbour clustering. Powerful sequence searching methods then enable structural assignments to be allocated to genomic data. \u0000 \u0000 \u0000 \u0000Key Concepts \u0000 \u0000Proteins comprise recognisable smaller sequence domains. \u0000Domains usually consist of secondary and supersecondary structures and have an average size of 150 ± 50 residues. \u0000These domains may be thought of as units of evolution, which recur in many proteins in various combinations. \u0000Structural classifications have been developed that group domains into fold and sequence families. \u0000The phenetic approach groups the proteins according to their structural characteristics. \u0000The phylogenetic approach groups proteins into families according to their evolutionary history. \u0000 \u0000 \u0000 \u0000 \u0000Keywords: \u0000 \u0000protein structure classification; \u0000common folds; \u0000protein architecture; \u0000structural comparison; \u0000genomes","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125642893","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 : 1900-01-01DOI: 10.1016/b978-0-12-809633-8.20505-0
Sanne Abeln, K. Feenstra, J. Heringa
{"title":"Protein Three-Dimensional Structure Prediction","authors":"Sanne Abeln, K. Feenstra, J. Heringa","doi":"10.1016/b978-0-12-809633-8.20505-0","DOIUrl":"https://doi.org/10.1016/b978-0-12-809633-8.20505-0","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114987328","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 : 1900-01-01DOI: 10.1016/B978-0-12-809633-8.20375-0
F. Marozzo, Paolo Trunfio
{"title":"Infrastructures for High-Performance Computing: Cloud Computing Development Environments","authors":"F. Marozzo, Paolo Trunfio","doi":"10.1016/B978-0-12-809633-8.20375-0","DOIUrl":"https://doi.org/10.1016/B978-0-12-809633-8.20375-0","url":null,"abstract":"","PeriodicalId":165920,"journal":{"name":"Encyclopedia of Bioinformatics and Computational Biology","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125235577","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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