Skip To Main Content
Limeng Pu on Muck Rack

Limeng Pu

As seen in: Nature, MDPI, BioRxiv
Is this you? As a journalist, you can create a free Muck Rack account to customize your profile, list your contact preferences, and upload a portfolio of your best work. Claim your profile
Back to Limeng Pu’s profile

Articles by Limeng Pu

High-resolution single-cell mapping of clonal hematopoiesis and structural variation in aplastic anemia

|
By Masanori Yoshida, Sushree S. Sahoo, Paula Arnold, Carmelo Gurnari, Anaïs van Leeuwen, Limeng Pu, Ti-Cheng Chang, Rashid Mehmood, Nathan Gray, Michelle Boals, Sara Lewis, Lili Kotmayer, Swapna Thota, Wenchao Zhang, Yichao Li, Emily Walker, Christy W. LaFlamme, Heather C Mefford, Zachary Brady, Yash Shah, Miriam Erlacher, Brigitte Strahm, Ayami Yoshimi, Shinsuke Hirabayashi, Helen Reed, Akiko Shimamura, Guolian Kang, Xiang Chen, Jinghui Zhang, Charlotte M. Niemeyer, Joseph H. Oved, Timothy Olson, Ruben van Boxtel, Jaroslaw Maciejewski, Daria V. Babushok, Marcin Wlodarski, Markus J. van Roosmalen, Charnise Goodings, Lucca L. M. Derks, Cristyn N. Branstetter, Joshua Leow, Melanie R. Loyd, Granger Ridout, Rheanna G. Congdon
| Nature Verified
Abstract Aplastic anemia (AA) results from T-cell-mediated destruction of hematopoietic stem and progenitor cells (HSPCs), driving clonal hematopoiesis via loss of human leukocyte antigen (HLA) risk alleles (HLA loss-of-function mutations or uniparental disomy 6p, UPD6p), paroxysmal nocturnal hemoglobinuria and clonal hematopoiesis of indeterminate potential (CHIP) mutations.
Open in Who Shared Issue with article?

Unlocking the Potential of Kinase Targets in Cancer: Insights from CancerOmicsNet, an AI-Driven Approach to Drug Response Prediction in Cancer

|
By Manali Singha, Limeng Pu, Gopal N Srivastava, Xialong Ni
| MDPI
Abstract : Simple Summary Protein kinases, which are molecules involved in cell growth and signaling, can go haywire in cancer cells, causing them to multiply uncontrollably. Using drugs to target these kinases shows promise for cancer treatment, but we still have a lot to learn about effectively targeting them. To prioritize kinases to focus on, we developed CancerOmicsNet, an artificial intelligence model that predicts the response of cancer cells to kinase inhibitor treatment.
Open in Who Shared Issue with article?

Graphsite: Ligand-binding site classification using Deep Graph Neural Network

|
By Wentao Shi, Manali Singha, Limeng Pu, J. Ramanujam
| BioRxiv
New Results Wentao Shi, Manali Singha, Limeng Pu, J. Ramanujam, Michal Brylinski doi: https://doi.org/10.1101/2021.12.06.471420 Abstract Binding sites are concave surfaces on proteins that bind to small molecules called ligands. Types of molecules that bind to the protein determine its biological function. Meanwhile, the binding process between small molecules and the protein is also crucial to various biological functionalities.
Open in Who Shared Issue with article?
Show More