Author

L. Crawford

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 Biophysics· 1 Cancer Biology· 1 Microbiology· 1

Signature Assays, Organisms & Methods

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Approach:experimental assay· 3 Organism:human· 2 Research Focus:cell type annotation· 1 Research Focus:clustering· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Research Focus:host-pathogen & immune response· 1

Frequent Co-Authors

K. K. Yang· 2 shared A. A. Borah· 1 shared A. D. Cherniack· 1 shared A. DenAdel· 1 shared A. Dias Costa· 1 shared A. J. Aguirre· 1 shared A. K. Shalek· 1 shared A. M. Jaeger· 1 shared

Activity by Year

2020-2023 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 36 mutual co-author links

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2 shared papersBioengineering

K. K. Yang

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4 papers

Recent·Most cited

UL135 and UL136 Epistasis Controls Reactivation of Human Cytomegalovirus

M. A. Moy, D. K. Collins-McMillen, L. Crawford, C. Parkins, S. Zeltzer, K. Caviness, P. Caposio, F. Goodrum

This study shows that stabilizing UL136p33 compensates for the loss of UL135 in HCMV reactivation from latency in hematopoietic cells.

bioRxiv · Jan 24, 2023 · PreprintMicrobiology

Randomized gates eliminate bias in sort-seq assays

B. L. Trippe, B. Huang, E. A. DeBenedictis, B. Coventry, N. Bhattacharya, K. K. Yang, D. Baker, L. Crawford

The paper introduces randomized sorting in sort-seq assays to eliminate systematic bias, validated through simulation and experiments, and extends the method for variance estimation and multi-bin sorting.

bioRxiv · Feb 17, 2022Bioengineering

A Topological Data Analytic Approach for Discovering Biophysical Signatures in Protein Dynamics

W. S. Tang, G. M. da Silva, H. Kirveslahti, E. Skeens, B. Feng, T. Sudijono, K. K. Yang, S. Mukherjee, B. Rubenstein, L. Crawford

SINATRA Pro identifies topological differences between protein structures from molecular dynamics simulations, revealing both known and novel biophysical signatures with improved resolution.

bioRxiv · Jul 28, 2021Biophysics

The tumor microenvironment drives transcriptional phenotypes and their plasticity in metastatic pancreatic cancer

S. Raghavan, P. S. Winter, A. W. Navia, H. L. Williams, A. DenAdel, R. L. Kalekar, J. Galvez-Reyes, K. E. Lowder, N. Mulugeta, M. S. Raghavan, A. A. Borah, K. S. Kapner, S. A. Vayrynen, A. Dias Costa, R. W. S. Ng, , A. K. Shalek

This study identifies a transitional cancer cell state in metastatic pancreatic cancer and shows that tumor microenvironment signals drive transcriptional plasticity and subtype transitions.

bioRxiv · Aug 25, 2020 · PreprintCancer Biology