Shoba Ranganathan
computational biologist
Facts
9 properties- Instance of
- human
- Occupation
- bioinformatician
- Employer
- Macquarie University, National University of Singapore, National University of Singapore, National University of Singapore, Macquarie University, University of Sydney, John Curtin School of Medical Research, University of Sydney, Jawaharlal Nehru University, University of Delhi, LSU New Orleans, Institut de biologie physico-chimique, CSIRO Health and Biosecurity
- Educated at
- Indian Institutes of Technology, Indian Institute of Technology Madras, University of Madras
- Official website
- researchers.mq.edu.au[5]
- Family name
- Ranganathan[4]
🏷️ Also known as
en Shoba Ranganathan
🔖 Identifiers · 25
- ISNI
- 0000000038702973
- ORCID iD
- 0000-0002-8290-813X
- VIAF cluster ID
- 51219899
- Library of Congress Authorities ID
- nb2008002688
- GND ID
- 1175593982
- Image (Wikimedia Commons)
- Shoba.jpg ↗
- Bibliothèque nationale de France ID
- 16728214s
- Canadiana Name Authority ID
- ncf11489989
- CiNii Research ID
- 1140845216725623168
- DBLP author ID
- r/ShobaRanganathan
- DDB person (GND) ID
- 1175593982
- Dimensions author ID
- 0657306270.28
Show all 25 identifiers +13
- Google Scholar author ID
- EYUeEfYAAAAJ
- IdRef ID
- 267924607
- J9U entity ID
- 987007437548005171
- LinkedIn personal profile ID
- shoba-ranganathan-9ab40718
- Loop ID
- 32091
- NACSIS-CAT author ID
- DA19233682
- NLA Trove people ID
- 1513629
- NUKAT ID
- n2017007820
- Nationale Thesaurus voor Auteursnamen ID
- 322501954
- Scopus author ID
- 55577597300, 56875665600
- Springer Nature person ID
- 0657306270.28
- WorldCat Entities ID
- E39PBJrm9vDPFH9fcXfMy4QrMP
- Yale LUX ID
- person/ebd221fb-7064-456c-b815-140ea39230c6
🔗 Connections
Author of 4
BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling,
Enhancing protein backbone angle prediction by using simpler models of deep neural networks,
Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors,
Prediction of interface residue based on the features of residue interaction network
← Authored by 4
BIO-GATS: A Tool for Automated GPCR Template Selection Through a Biophysical Approach for Homology Modeling,
Enhancing protein backbone angle prediction by using simpler models of deep neural networks,
Machine Learning Assisted Approach for Finding Novel High Activity Agonists of Human Ectopic Olfactory Receptors,
Prediction of interface residue based on the features of residue interaction network
Affiliated with 1
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