Nicht aus der Schweiz? Besuchen Sie lehmanns.de
Machine Learning and Systems Biology in Genomics and Health -

Machine Learning and Systems Biology in Genomics and Health (eBook)

Shailza Singh (Herausgeber)

eBook Download: PDF
2022 | 1st ed. 2022
VII, 236 Seiten
Springer Singapore (Verlag)
978-981-16-5993-5 (ISBN)
Systemvoraussetzungen
234,33 inkl. MwSt
(CHF 228,90)
Der eBook-Verkauf erfolgt durch die Lehmanns Media GmbH (Berlin) zum Preis in Euro inkl. MwSt.
  • Download sofort lieferbar
  • Zahlungsarten anzeigen
This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. 

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.
This book discusses the application of machine learning in genomics. Machine Learning offers ample opportunities for Big Data to be assimilated and comprehended effectively using different frameworks. Stratification, diagnosis, classification and survival predictions encompass the different health care regimes representing unique challenges for data pre-processing, model training, refinement of the systems with clinical implications. The book discusses different models for in-depth analysis of different conditions. Machine Learning techniques have revolutionized genomic analysis. Different chapters of the book describe the role of Artificial Intelligence in clinical and genomic diagnostics. It discusses how systems biology is exploited in identifying the genetic markers for drug discovery and disease identification. Myriad number of diseases whether be infectious, metabolic, cancer can be dealt in effectively which combines the different omics data for precision medicine. Major breakthroughs in the field would help reflect more new innovations which are at their pinnacle stage. This book is useful for researchers in the fields of genomics, genetics, computational biology and bioinformatics.
Erscheint lt. Verlag 4.2.2022
Zusatzinfo VII, 236 p. 1 illus.
Sprache englisch
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-10 981-16-5993-1 / 9811659931
ISBN-13 978-981-16-5993-5 / 9789811659935
Haben Sie eine Frage zum Produkt?
PDFPDF (Wasserzeichen)
Größe: 5,7 MB

DRM: Digitales Wasserzeichen
Dieses eBook enthält ein digitales Wasser­zeichen und ist damit für Sie persona­lisiert. Bei einer missbräuch­lichen Weiter­gabe des eBooks an Dritte ist eine Rück­ver­folgung an die Quelle möglich.

Dateiformat: PDF (Portable Document Format)
Mit einem festen Seiten­layout eignet sich die PDF besonders für Fach­bücher mit Spalten, Tabellen und Abbild­ungen. Eine PDF kann auf fast allen Geräten ange­zeigt werden, ist aber für kleine Displays (Smart­phone, eReader) nur einge­schränkt geeignet.

Systemvoraussetzungen:
PC/Mac: Mit einem PC oder Mac können Sie dieses eBook lesen. Sie benötigen dafür einen PDF-Viewer - z.B. den Adobe Reader oder Adobe Digital Editions.
eReader: Dieses eBook kann mit (fast) allen eBook-Readern gelesen werden. Mit dem amazon-Kindle ist es aber nicht kompatibel.
Smartphone/Tablet: Egal ob Apple oder Android, dieses eBook können Sie lesen. Sie benötigen dafür einen PDF-Viewer - z.B. die kostenlose Adobe Digital Editions-App.

Buying eBooks from abroad
For tax law reasons we can sell eBooks just within Germany and Switzerland. Regrettably we cannot fulfill eBook-orders from other countries.

Mehr entdecken
aus dem Bereich
Entstehung, Progression und Therapie von Krebs

von Christoph Wagener; Oliver Müller

eBook Download (2022)
Thieme (Verlag)
CHF 195,35
Entstehung, Progression und Therapie von Krebs

von Christoph Wagener; Oliver Müller

eBook Download (2022)
Thieme (Verlag)
CHF 195,35
Handbuch für die Pflegepraxis

von Thomas Kroner; Anita Margulies; Sacha Rothschild …

eBook Download (2023)
Springer Berlin Heidelberg (Verlag)
CHF 29,30