Analyzing Network Data in Biology and Medicine
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Analyzing Network Data in Biology and Medicine
An Interdisciplinary Textbook for Biological, Medical and Computational Scientists
Przulj, Natasa
Cambridge University Press
03/2019
643
Mole
Inglês
9781108432238
15 a 20 dias
1280
Descrição não disponível.
1. From genetic data to medicine: from DNA samples to disease risk prediction in personalized genetic tests Luis Leal, Rok Kosir and Natasa Przulj; 2. Epigenetic data and disease Rodrigo Gonzalez-Barrios, Marisol Salgado-Albarran, Nicolas Alcaraz, Cristian Arriaga-Canon, Lissania Guerra-Calderas, Laura Contreras-Espinoza and Ernesto Soto-Reyes; 3. Introduction to graph and network theory Thomas Gaudelet and Natasa Przulj; 4. Protein-protein interaction data, their quality, and major public databases Anne-Christin Hauschild, Chiara Pastrello, Max Kotlyar and Igor Jurisica; 5. Graphlets in network science and computational biology Khalique Newaz and Tijana Milenkovic; 6. Cluster analysis Richard Roettger; 7. Machine learning for data integration in cancer precision medicine: matrix factorization approaches Noel Malod-Dognin, Sam Windels and Natasa Przulj; 8. Machine learning for biomarker discovery: significant pattern mining F. Llinares-Lopez and K. Borgwardt; 9. Network alignment Noel Malod-Dogning and Natasa Przulj; 10. Network medicine Pisanu Buphamalai, Michael Caldera, Felix Mueller and Joerg Menche; 11. Elucidating genotype-to-phenotype relationships via analyzes of human tissue interactomes Idan Hekselman, Moran Sharon, Omer Basha and Esti Yeger-Lotem; 12. Network neuroscience Alberto Cacciola, Alessandro Muscoloni and Carlo Vittorio Cannistraci; 13. Cytoscape: tool for analyzing and visualizing network data John H. Morris; 14. Analysis of the signatures of cancer stem cells in malignant tumours using protein interactomes and STRING database Kresimir Pavelic, Marko Klobucar, Dolores Kuzelj, Natasa Przulj and Sandra Kraljevic Pavelic.
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1. From genetic data to medicine: from DNA samples to disease risk prediction in personalized genetic tests Luis Leal, Rok Kosir and Natasa Przulj; 2. Epigenetic data and disease Rodrigo Gonzalez-Barrios, Marisol Salgado-Albarran, Nicolas Alcaraz, Cristian Arriaga-Canon, Lissania Guerra-Calderas, Laura Contreras-Espinoza and Ernesto Soto-Reyes; 3. Introduction to graph and network theory Thomas Gaudelet and Natasa Przulj; 4. Protein-protein interaction data, their quality, and major public databases Anne-Christin Hauschild, Chiara Pastrello, Max Kotlyar and Igor Jurisica; 5. Graphlets in network science and computational biology Khalique Newaz and Tijana Milenkovic; 6. Cluster analysis Richard Roettger; 7. Machine learning for data integration in cancer precision medicine: matrix factorization approaches Noel Malod-Dognin, Sam Windels and Natasa Przulj; 8. Machine learning for biomarker discovery: significant pattern mining F. Llinares-Lopez and K. Borgwardt; 9. Network alignment Noel Malod-Dogning and Natasa Przulj; 10. Network medicine Pisanu Buphamalai, Michael Caldera, Felix Mueller and Joerg Menche; 11. Elucidating genotype-to-phenotype relationships via analyzes of human tissue interactomes Idan Hekselman, Moran Sharon, Omer Basha and Esti Yeger-Lotem; 12. Network neuroscience Alberto Cacciola, Alessandro Muscoloni and Carlo Vittorio Cannistraci; 13. Cytoscape: tool for analyzing and visualizing network data John H. Morris; 14. Analysis of the signatures of cancer stem cells in malignant tumours using protein interactomes and STRING database Kresimir Pavelic, Marko Klobucar, Dolores Kuzelj, Natasa Przulj and Sandra Kraljevic Pavelic.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
