Semantic Scholar Open Access 2018 802 sitasi

Next-Generation Machine Learning for Biological Networks.

Diogo M. Camacho K. M. Collins Rani K. Powers J. Costello J. Collins

Lihat Sumber DOI

Abstrak

Machine learning, a collection of data-analytical techniques aimed at building predictive models from multi-dimensional datasets, is becoming integral to modern biological research. By enabling one to generate models that learn from large datasets and make predictions on likely outcomes, machine learning can be used to study complex cellular systems such as biological networks. Here, we provide a primer on machine learning for life scientists, including an introduction to deep learning. We discuss opportunities and challenges at the intersection of machine learning and network biology, which could impact disease biology, drug discovery, microbiome research, and synthetic biology.

Topik & Kata Kunci

Medicine Biology

Penulis (5)

Diogo M. Camacho

K. M. Collins

Rani K. Powers

J. Costello

J. Collins

Format Sitasi

APA MLA BibTeX

Camacho, D.M., Collins, K.M., Powers, R.K., Costello, J., Collins, J. (2018). Next-Generation Machine Learning for Biological Networks.. https://doi.org/10.1016/j.cell.2018.05.015

Akses Cepat

Lihat di Sumber doi.org/10.1016/j.cell.2018.05.015

Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Total Sitasi: 802×
Sumber Database: Semantic Scholar
DOI: 10.1016/j.cell.2018.05.015
Akses: Open Access ✓