Synopsis
Successful Prediction for Major Histocompatibility Complex (MHC) molecule epitopes is an essential step in designing Genetic Vaccines. Successful prediction of MHC class II epitopes is more difficult than MHC class I epitopes due to open binding groove at both ends in class II molecules, this structure leads to variable length for MHC II epitopes and complicating the task for detecting the core binding 9-mer. In this Book we presented a novel classification algorithm for predicting MHC Class II epitopes using Multiple Instance Learning technique. Separated Constructive Clustering Ensemble (SCCE) is our new version for Constructive Clustering Ensemble (CCE). SCCE integrated Genetic Algorithm, K medoid clustering, Ensemble learning and Support vector machine in an orchestration to predict the MHC II epitopes. SCCE is tested by four benchmark data sets and achieved average accuracy 85%. SCCE results exceed most of the current state of art regression methods. SCCE achieved these results using only binder and non-binder flags, without need for regression data.
"synopsis" may belong to another edition of this title.
About the Author
Hossam Elsemellawy is Researcher in the Arab Academy for Science, Technology and Maritime Transport, Egypt. Amr Badr is a Prof. of Computer Science, Cairo University, Egypt. Mostafa Abdelazim is a Prof. of Computer Science in the Arab Academy for Science, Technology and Maritime Transport, Egypt.
"About this title" may belong to another edition of this title.
Search results for Immunological Bioinformatics: Predicting MHC Class...
Seller Image
Immunological Bioinformatics
Published by
LAP LAMBERT Academic Publishing Okt 2015, 2015
ISBN 10: 3659792489
ISBN 13: 9783659792489
New
Taschenbuch
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Successful Prediction for Major Histocompatibility Complex (MHC) molecule epitopes is an essential step in designing Genetic Vaccines. Successful prediction of MHC class II epitopes is more difficult than MHC class I epitopes due to open binding groove at both ends in class II molecules, this structure leads to variable length for MHC II epitopes and complicating the task for detecting the core binding 9-mer. In this Book we presented a novel classification algorithm for predicting MHC Class II epitopes using Multiple Instance Learning technique. Separated Constructive Clustering Ensemble (SCCE) is our new version for Constructive Clustering Ensemble (CCE). SCCE integrated Genetic Algorithm, K medoid clustering, Ensemble learning and Support vector machine in an orchestration to predict the MHC II epitopes. SCCE is tested by four benchmark data sets and achieved average accuracy 85%. SCCE results exceed most of the current state of art regression methods. SCCE achieved these results using only binder and non-binder flags, without need for regression data. 104 pp. Englisch. Seller Inventory # 9783659792489
Seller Image
Immunological Bioinformatics
Published by
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659792489
ISBN 13: 9783659792489
New
Softcover
Seller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Elsemellawy HossamHossam Elsemellawy is Researcher in the Arab Academy for Science, Technology and Maritime Transport, Egypt. Amr Badr is a Prof. of Computer Science, Cairo University, Egypt. Mostafa Abdelazim is a Prof. of Computer . Seller Inventory # 158429523
Buy New
£ 40.32
£ 42.20 shipping
Ships from Germany to U.S.A.
Ships from Germany to U.S.A.
Quantity: Over 20 available
Seller Image
Immunological Bioinformatics
Published by
LAP LAMBERT Academic Publishing Okt 2015, 2015
ISBN 10: 3659792489
ISBN 13: 9783659792489
New
Taschenbuch
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Successful Prediction for Major Histocompatibility Complex (MHC) molecule epitopes is an essential step in designing Genetic Vaccines. Successful prediction of MHC class II epitopes is more difficult than MHC class I epitopes due to open binding groove at both ends in class II molecules, this structure leads to variable length for MHC II epitopes and complicating the task for detecting the core binding 9-mer. In this Book we presented a novel classification algorithm for predicting MHC Class II epitopes using Multiple Instance Learning technique. Separated Constructive Clustering Ensemble (SCCE) is our new version for Constructive Clustering Ensemble (CCE). SCCE integrated Genetic Algorithm, K medoid clustering, Ensemble learning and Support vector machine in an orchestration to predict the MHC II epitopes. SCCE is tested by four benchmark data sets and achieved average accuracy 85%. SCCE results exceed most of the current state of art regression methods. SCCE achieved these results using only binder and non-binder flags, without need for regression data.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch. Seller Inventory # 9783659792489
Seller Image
Immunological Bioinformatics : Predicting MHC Class II Epitopes
Published by
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659792489
ISBN 13: 9783659792489
New
Taschenbuch
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Successful Prediction for Major Histocompatibility Complex (MHC) molecule epitopes is an essential step in designing Genetic Vaccines. Successful prediction of MHC class II epitopes is more difficult than MHC class I epitopes due to open binding groove at both ends in class II molecules, this structure leads to variable length for MHC II epitopes and complicating the task for detecting the core binding 9-mer. In this Book we presented a novel classification algorithm for predicting MHC Class II epitopes using Multiple Instance Learning technique. Separated Constructive Clustering Ensemble (SCCE) is our new version for Constructive Clustering Ensemble (CCE). SCCE integrated Genetic Algorithm, K medoid clustering, Ensemble learning and Support vector machine in an orchestration to predict the MHC II epitopes. SCCE is tested by four benchmark data sets and achieved average accuracy 85%. SCCE results exceed most of the current state of art regression methods. SCCE achieved these results using only binder and non-binder flags, without need for regression data. Seller Inventory # 9783659792489
Seller Image
Immunological Bioinformatics | Predicting MHC Class II Epitopes
Published by
LAP LAMBERT Academic Publishing, 2015
ISBN 10: 3659792489
ISBN 13: 9783659792489
New
Taschenbuch
Seller: preigu, Osnabrück, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. Immunological Bioinformatics | Predicting MHC Class II Epitopes | Hossam Elsemellawy (u. a.) | Taschenbuch | 104 S. | Englisch | 2015 | LAP LAMBERT Academic Publishing | EAN 9783659792489 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Seller Inventory # 104146853