Core Metrics
Total Citations
2,042
H-Index
18
Publications
36
i10-Index
24
2-Year Citedness
0.0
avg citations per work
Ability Dimensions
2,042 citations, h=18
Based on publication trend
36 papers (2.4/year)
57 cites/paper
1 unique research topics
5 topic areas
Top 3 papers: 50% of citations
* Percentile scores are calculated relative to all scholars in the computational neuroscience dataset. Tags are assigned based on dimension combinations. Hover over the radar chart for details.
Scholar Profile Analysis
Garrett B. Goh is a emerging scholar in computational neuroscience, currently affiliated with Pacific Northwest National Laboratory.
Over a 15-year academic career, published 36 papers (averaging 2.4 per year), with 2,042 citations.
Primary research areas include Gene, Gene, Gene.
Key Findings
Signature Work
"Deep learning for computational chemistry" is the most influential work, with 774 citations, published in 2017.
Early Career Analysis (First 5 Years)
Career Start
2010 - 2014
Early Citations
559
Early Works
9
Early Impact %
27.4%
Top Early Career Paper
Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism
Publication Timeline
Research Topics
Top Publications
Deep learning for computational chemistry
774
Citations
Constant pH molecular dynamics of proteins in explicit solvent with proton tautomerism
128
Citations
Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models
115
Citations
Characterizing the Protonation State of Cytosine in Transient G·C Hoogsteen Base Pairs in Duplex DNA
108
Citations
Constant pH Molecular Dynamics Simulations of Nucleic Acids in Explicit Solvent
108
Citations
Chemception: A Deep Neural Network with Minimal Chemistry Knowledge\n Matches the Performance of Expert-developed QSAR/QSPR Models
106
Citations
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for\n Predicting Chemical Properties
90
Citations