Predicting the Lineage Choice of Hematopoietic Stem Cells: A Novel Approach Using Deep Neural Networks - Couverture souple

Kroiss, Manuel

Couverture souple

ISBN 10 : 365812878X ISBN 13 : 9783658128784

Editeur : Springer Spektrum, 2016

Synopsis

Manuel Kroiss examines the differentiation of hematopoietic stem cells using machine learning methods. This work is based on experiments focusing on the lineage choice of CMPs, the progenitors of HSCs, which either become MEP or GMP cells. The author presents a novel approach to distinguish MEP from GMP cells using machine learning on morphology features extracted from bright field images. He tests the performance of different models and focuses on Recurrent Neural Networks with the latest advances from the field of deep learning. Two different improvements to recurrent networks were tested: Long Short Term Memory (LSTM) cells that are able to remember information over long periods of time, and dropout regularization to prevent overfitting. With his method, Manuel Kroiss considerably outperforms standard machine learning methods without time information like Random Forests and Support Vector Machines.

A propos du livre

À propos de l'auteur

After finishing his MSc in Bioinformatics, Manuel Kroiss moved to London to work for a computer science company. In his work, the author is focusing on algorithmic problem solving while still remaining interested in applied machine learning.

Détails de l'édition

• Éditeur: Springer Spektrum
• Date d'édition: 2016
• Langue: anglais
• ISBN 10: 365812878X
• ISBN 13: 9783658128784
• Reliure: Broché
• Numéro d'édition: 1
• Nombre de pages: 84
• Coordonnées du fabricant: Springer Nature Customer Service Center GmbH; ProductSafety@springernature.com; ; Europaplatz 3; Heidelberg; 69115; Allemagne