Raghav, N and Vishnu GK, A and Deshpande, N and Rangarajan, A (2024) Introduction to machine learning and its applications in stem cell research. [Book Chapter]
Full text not available from this repository. (Request a copy)Abstract
Machine learning (ML) is a branch of artificial intelligence that aims to develop models/algorithms that can �learn� a task from data (training data) and subsequently provide predictions on unseen data (test data). Recent developments in ML algorithms, specifically deep learning, have opened new prospects for computational biology�a transdiscipline resulting from the amalgamation of biology and computer science. Presently, deep learning algorithms can analyze and process vast amounts of data, both structured and unstructured, generated through high-throughput technologies. Thus, they are being widely applied in diverse fields of biology, including stem cell research. In this chapter, we discuss the applications of ML algorithms in stem cell research. We begin with a brief introduction to stem cells and then discuss neural networks, deep learning models, and their applications in stem cell research. We conclude the chapter with a brief discussion on the current challenges and future directions of the field. © 2024 Elsevier Inc. All rights reserved.
| Item Type: | Book Chapter |
|---|---|
| Publication: | Computational Biology for Stem Cell Research |
| Publisher: | Elsevier |
| Additional Information: | The copyright for this article belongs to Elsevier. |
| Department/Centre: | Division of Biological Sciences > Molecular Reproduction, Development & Genetics Division of Interdisciplinary Sciences > Centre for Biosystems Science and Engineering Division of Interdisciplinary Sciences > Interdisciplinary Mathematical Sciences |
| Date Deposited: | 14 Sep 2024 11:36 |
| Last Modified: | 14 Sep 2024 11:36 |
| URI: | http://eprints.iisc.ac.in/id/eprint/84902 |
Actions (login required)
 |
View Item |
