Deep Learning with Microfluidics for Biotechnology.

Biotechnology / methods Deep Learning Microfluidics / methods
deep learning lab-on-a-chip machine learning microfluidics

Journal

Trends in biotechnology
ISSN: 1879-3096
Titre abrégé: Trends Biotechnol
Pays: England
ID NLM: 8310903

Informations de publication

Date de publication:
03 2019
Historique:
received: 20 06 2018
revised: 22 08 2018
accepted: 23 08 2018
pubmed: 12 10 2018
medline: 18 12 2019
entrez: 11 10 2018
Statut: ppublish

Résumé

Advances in high-throughput and multiplexed microfluidics have rewarded biotechnology researchers with vast amounts of data but not necessarily the ability to analyze complex data effectively. Over the past few years, deep artificial neural networks (ANNs) leveraging modern graphics processing units (GPUs) have enabled the rapid analysis of structured input data - sequences, images, videos - to predict complex outputs with unprecedented accuracy. While there have been early successes in flow cytometry, for example, the extensive potential of pairing microfluidics (to acquire data) and deep learning (to analyze data) to tackle biotechnology challenges remains largely untapped. Here we provide a roadmap to integrating deep learning and microfluidics in biotechnology laboratories that matches computational architectures to problem types, and provide an outlook on emerging opportunities.

Identifiants

DOI: 10.1016/j.tibtech.2018.08.005 PMID: 30301571
pubmed: 30301571
pii: S0167-7799(18)30245-2
doi: 10.1016/j.tibtech.2018.08.005
pii:
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't Review

Langues

eng

Sous-ensembles de citation

IM

Pagination

310-324

Subventions

Organisme : CIHR
Pays : Canada

Informations de copyright

Copyright © 2018 Elsevier Ltd. All rights reserved.

Auteurs

Jason Riordon (J)

Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada.

Dušan Sovilj (D)

Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada.

Scott Sanner (S)

Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada; http://d3m.mie.utoronto.ca/.

David Sinton (D)

Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada; http://www.sintonlab.com/.

Edmond W K Young (EWK)

Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON, Canada; http://ibmt.mie.utoronto.ca/. Electronic address: eyoung@mie.utoronto.ca.

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Classifications MeSH

questionsmedicales.fr › Technologie, industrie et agriculture › Technologie › Biotechnologie › Deep Learning with Microfluidics for Biotechnology.
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Réseaux neuronaux (ordinateur) › Apprentissage profond › Deep Learning with Microfluidics for Biotechnology.
questionsmedicales.fr › Technologie, industrie et agriculture › Technologie › Miniaturisation › Microtechnologie › Microfluidique › Deep Learning with Microfluidics for Biotechnology.