Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

CASTLE: A database of synthetic lethal sets predicted from genome-scale metabolic networks

Vimaladhasan Senthamizhan, Sunanda Subramaniam, Arjun Raghavan, View ORCID ProfileKarthik Raman
doi: https://doi.org/10.1101/2021.02.08.430024
Vimaladhasan Senthamizhan
1Initiative for Biological Systems Engineering, IIT Madras, Chennai - 600 036, India
2Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras, Chennai - 600 036, India
3Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai - 600 036, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Sunanda Subramaniam
1Initiative for Biological Systems Engineering, IIT Madras, Chennai - 600 036, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Arjun Raghavan
3Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai - 600 036, India
4Department of Biomedical Engineering, McMaster University, Hamilton, ON, Canada. Present address: University of Manitoba, Winnipeg, Canada
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Karthik Raman
1Initiative for Biological Systems Engineering, IIT Madras, Chennai - 600 036, India
2Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras, Chennai - 600 036, India
3Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai - 600 036, India
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Karthik Raman
  • For correspondence: kraman@iitm.ac.in
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading
  • Supplementary Table[supplements/430024_file05.csv]
Back to top
PreviousNext
Posted February 08, 2021.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
CASTLE: A database of synthetic lethal sets predicted from genome-scale metabolic networks
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
CASTLE: A database of synthetic lethal sets predicted from genome-scale metabolic networks
Vimaladhasan Senthamizhan, Sunanda Subramaniam, Arjun Raghavan, Karthik Raman
bioRxiv 2021.02.08.430024; doi: https://doi.org/10.1101/2021.02.08.430024
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
CASTLE: A database of synthetic lethal sets predicted from genome-scale metabolic networks
Vimaladhasan Senthamizhan, Sunanda Subramaniam, Arjun Raghavan, Karthik Raman
bioRxiv 2021.02.08.430024; doi: https://doi.org/10.1101/2021.02.08.430024

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Systems Biology
Subject Areas
All Articles
  • Animal Behavior and Cognition (3689)
  • Biochemistry (7789)
  • Bioengineering (5674)
  • Bioinformatics (21282)
  • Biophysics (10576)
  • Cancer Biology (8173)
  • Cell Biology (11937)
  • Clinical Trials (138)
  • Developmental Biology (6762)
  • Ecology (10401)
  • Epidemiology (2065)
  • Evolutionary Biology (13863)
  • Genetics (9708)
  • Genomics (13070)
  • Immunology (8139)
  • Microbiology (19983)
  • Molecular Biology (7842)
  • Neuroscience (43053)
  • Paleontology (319)
  • Pathology (1279)
  • Pharmacology and Toxicology (2258)
  • Physiology (3351)
  • Plant Biology (7232)
  • Scientific Communication and Education (1312)
  • Synthetic Biology (2004)
  • Systems Biology (5537)
  • Zoology (1128)