Author

W. Pang

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 1 Evolutionary Biology· 1

Signature Assays, Organisms & Methods

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Approach:deep learning· 1 Assay:DNA methylation· 1 Organism:E. coli· 1 Research Focus:genome assembly· 1 Organism:human· 1 Approach:machine learning (classical)· 1 Research Focus:variant effect prediction· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

A. K. Chakraborty· 1 shared C. S. Grierson· 1 shared I. M. Gherman· 1 shared J. O. Lloyd-Smith· 1 shared J. P. Barton· 1 shared J. P. Rees-Garbutt· 1 shared K. Sharma· 1 shared L. Dai· 1 shared

Activity by Year

2019-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 20 mutual co-author links

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1 shared paperEvolutionary Biology

A. K. Chakraborty

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2 papers

Recent·Most cited

Accelerated design of Escherichia coli genomes with reduced size using a whole-cell model and machine learning

I. M. Gherman, K. Sharma, J. P. Rees-Garbutt, W. Pang, Z. S. Abdallah, T. E. Gorochowski, C. S. Grierson, L. Marucci

The paper uses a whole-cell model and machine learning to design a reduced E. coli genome with 40% fewer genes, achieving 95% faster computation.

bioRxiv · Oct 30, 2023Bioengineering

Predominance of positive epistasis among drug resistance-associated mutations in HIV-1 protease

T.-h. Zhang, L. Dai, J. P. Barton, Y. Du, Y. Tan, W. Pang, A. K. Chakraborty, J. O. Lloyd-Smith, R. Sun

The paper profiles the fitness landscape of HIV-1 protease resistance mutations and finds that positive epistasis is predominant, reducing the likelihood of reversing drug resistance mutations.

bioRxiv · Oct 31, 2019Evolutionary Biology