Machine Learning and Systems Biology in Genomics and Health
Springer Verlag, Singapore
978-981-16-5992-8 (ISBN)
This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.
Dr. Shailza Singh is Scientist-E and Incharge of Bioinformatics and High Performance Computing Facility, National Centre for Cell Science, Pune, India Her research chiefly focuses on systems and synthetic biology. She also specializes in infectious diseases such as leishmaniasis. Her research group is working to integrate the action of regulatory circuits, cross-talk between pathways, and non-linear kinetics of biochemical processes through mathematical modeling. Dr. Singh has been honored with the DBT-RGYI, DST Young Scientist and INSA Bilateral Exchange Programme awards, and was selected by the DBT for a SAKURA EXCHANGE Programme in Science in the field of Artificial Intelligence and Machine learning to Tokyo in 2018. She serves as a reviewer for prestigious international grants such as the Research Councils UK; for national grants from the DBT, DST and CSIR; and for several prominent international journals, e.g. Parasite and Vectors, PLOS One, BMC Infectious Disease, BMC Research Notes, Oncotarget, and the International Journal of Cancer.
Chapter 1: Construction of feedforward multilayer perceptron model for diagnosing leishmaniasis using transcriptome datasets and cognitive computing.- Chapter2- Big data in drug discovery.- Chapter3 - An overview of databases and tools for lncRNA genomics advancing precision medicine.- Chapter 4-Machine Learning in Genomics.- Chapter 5-How Machine Learning has revolutionized the field of Cancer Informatics?.- Chapter 6- Connecting the dots: Using machine learning to Forge Gene Regulatory Networks from large biological datasets.- Chapter 7-Identification of novel Non-coding RNAs in Plants by Big data analysis.- Chapter 8-Artificial Intelligence in Biomedical Image Processing.- Chapter 9- Artificial Intelligence and its Application in Cardiovascular Disease Management.
Erscheinungsdatum | 11.02.2022 |
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Zusatzinfo | 1 Illustrations, black and white; VII, 236 p. 1 illus. |
Verlagsort | Singapore |
Sprache | englisch |
Maße | 155 x 235 mm |
Themenwelt | Medizin / Pharmazie ► Medizinische Fachgebiete ► Onkologie |
Naturwissenschaften ► Biologie ► Genetik / Molekularbiologie | |
Schlagworte | big data genomics • Computational Biology • Deep learning • genomic analysis • random forest • systems biology |
ISBN-10 | 981-16-5992-3 / 9811659923 |
ISBN-13 | 978-981-16-5992-8 / 9789811659928 |
Zustand | Neuware |
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