9783847324348 - A Textbook on HIV AIDS: A System Biology Study de Kumar, Amrendar; Singh, Abhilasha; Agarwal, Mayank (6 resultados)

Taschenbuch. Condición: Neu. A Textbook on HIV AIDS | A System Biology Study | Amrendar Kumar (u. a.) | Taschenbuch | 188 S. | Englisch | 2012 | LAP LAMBERT Academic Publishing | EAN 9783847324348 | Verantwortliche Person für die EU: BoD - Books on Demand, In de Tarpen 42, 22848 Norderstedt, info[at]bod[dot]de | Anbieter: preigu.

Paperback. Condición: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -HIV is a member of the genus Lentivirus, part of the family of Retroviridae. Two types of HIV have been characterized: HIV-1 and HIV-2. HIV-1 is the most common and pathogenic strain of the virus. Despite the success of highly active antiretroviral therapy (HAART) in controlling HIV infection and reducing HIV associated mortality, current drug regimens are unable to completely eradicate HIV infection. Bioinformatics methods based on complex networks and Gene Ontologies (GOs) come to our rescue in predicting the possible targets for such diseases and are very useful in this area. This work reviews some bioinformatics concepts and previous studies related to HIV research using Gene Ontologies (GO), complex networks, and related methods. Also, we report new results mapping natural compounds on potential drug target for HIV network using GOs. The network is statistically analyzed and represented by the graphical interpretation to encounter the hub nodes and their locally parsed neighbors, ligands multi-receptor docking and the propensity of drug targets in hub nodes and related sub-networks. 188 pp. Englisch.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: kumar AmrendarAbhilasha Singh, she is doing B.Tech Bioinformatics from Amity University, Lucknow and is in 2008-12 batch.Amrendar kumar, he is doing B.Tech Biotechnology from Amity University, lucknow and is in 2008-2012 batch.Mayank.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -HIV is a member of the genus Lentivirus, part of the family of Retroviridae. Two types of HIV have been characterized: HIV-1 and HIV-2. HIV-1 is the most common and pathogenic strain of the virus. Despite the success of highly active antiretroviral therapy (HAART) in controlling HIV infection and reducing HIV associated mortality, current drug regimens are unable to completely eradicate HIV infection. Bioinformatics methods based on complex networks and Gene Ontologies (GOs) come to our rescue in predicting the possible targets for such diseases and are very useful in this area. This work reviews some bioinformatics concepts and previous studies related to HIV research using Gene Ontologies (GO), complex networks, and related methods. Also, we report new results mapping natural compounds on potential drug target for HIV network using GOs. The network is statistically analyzed and represented by the graphical interpretation to encounter the hub nodes and their locally parsed neighbors, ligands multi-receptor docking and the propensity of drug targets in hub nodes and related sub-networks.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 188 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - HIV is a member of the genus Lentivirus, part of the family of Retroviridae. Two types of HIV have been characterized: HIV-1 and HIV-2. HIV-1 is the most common and pathogenic strain of the virus. Despite the success of highly active antiretroviral therapy (HAART) in controlling HIV infection and reducing HIV associated mortality, current drug regimens are unable to completely eradicate HIV infection. Bioinformatics methods based on complex networks and Gene Ontologies (GOs) come to our rescue in predicting the possible targets for such diseases and are very useful in this area. This work reviews some bioinformatics concepts and previous studies related to HIV research using Gene Ontologies (GO), complex networks, and related methods. Also, we report new results mapping natural compounds on potential drug target for HIV network using GOs. The network is statistically analyzed and represented by the graphical interpretation to encounter the hub nodes and their locally parsed neighbors, ligands multi-receptor docking and the propensity of drug targets in hub nodes and related sub-networks.