Predicting the lineage choice of hematopoietic stem cells [electronic resource] : a novel approach using deep neural networks / Manuel Kroiss.
2016
QH588.S83
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Title
Predicting the lineage choice of hematopoietic stem cells [electronic resource] : a novel approach using deep neural networks / Manuel Kroiss.
Author
Kroiss, Manuel, author.
ISBN
9783658128791 (electronic book)
3658128798 (electronic book)
9783658128784
3658128798 (electronic book)
9783658128784
Published
Wiesbaden : Springer Spektrum, 2016.
Language
English
Description
1 online resource (xv, 68 pages).
Call Number
QH588.S83
Dewey Decimal Classification
616.02/774
Summary
Annotation 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.
Note
Annotation 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.
Bibliography, etc. Note
Includes bibliographical references.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed May 18, 2016).
Series
BestMasters.
Available in Other Form
Predicting the Lineage Choice of Hematopoietic Stem Cells : A Novel Approach Using Deep Neural Networks.
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Table of Contents
Machine Learning
Deep Learning
Training Neural Networks
Recurrent Neural Networks
Stem Cell Classification Using Microscopy Images.
Deep Learning
Training Neural Networks
Recurrent Neural Networks
Stem Cell Classification Using Microscopy Images.