Patrick J. Lawrence

403 total citations
9 papers, 284 citations indexed

About

Patrick J. Lawrence is a scholar working on Molecular Biology, Epidemiology and Computational Theory and Mathematics. According to data from OpenAlex, Patrick J. Lawrence has authored 9 papers receiving a total of 284 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Epidemiology and 2 papers in Computational Theory and Mathematics. Recurrent topics in Patrick J. Lawrence's work include Computational Drug Discovery Methods (2 papers), Congenital Heart Disease Studies (2 papers) and Congenital heart defects research (2 papers). Patrick J. Lawrence is often cited by papers focused on Computational Drug Discovery Methods (2 papers), Congenital Heart Disease Studies (2 papers) and Congenital heart defects research (2 papers). Patrick J. Lawrence collaborates with scholars based in United States, Somalia and Pakistan. Patrick J. Lawrence's co-authors include Qin Ma, Qingmei Zhang, Cheng Chen, Yan Zhang, Bin Yu, Zhaomin Yu, Zhenyu Wu, Robert C. Jones, Jian Zhu and Patrick K.C. Chun and has published in prestigious journals such as CHEST Journal, Trends in Pharmacological Sciences and PLoS Genetics.

In The Last Decade

Patrick J. Lawrence

9 papers receiving 272 citations

Peers

Patrick J. Lawrence

MB

CTM

PRM

AI

CCM

Joyeeta Dutta‐Moscato United States

Fleur Jeanquartier Austria

Jiahong Yang China

Zhen Tang China

Giovanna Nicora Italy

Domingo López-Rodríguez Spain

Truong Nguyen Khanh Hung Vietnam

JiaRui Li China

Christian Tiemann Netherlands

Kristin Tøndel Norway

Joyeeta Dutta‐Moscato United States

Patrick J. Lawrence

168 ×1.3

MB

16 ×0.4

CTM

21 ×0.6

PRM

19 ×0.6

AI

15 ×0.5

CCM

Citations per year, relative to Patrick J. Lawrence Patrick J. Lawrence (= 1×) peers Joyeeta Dutta‐Moscato

Countries citing papers authored by Patrick J. Lawrence

Since Specialization

Citations

This map shows the geographic impact of Patrick J. Lawrence's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Patrick J. Lawrence with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Patrick J. Lawrence more than expected).

Fields of papers citing papers by Patrick J. Lawrence

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patrick J. Lawrence. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Patrick J. Lawrence. The network helps show where Patrick J. Lawrence may publish in the future.

Co-authorship network of co-authors of Patrick J. Lawrence

This figure shows the co-authorship network connecting the top 25 collaborators of Patrick J. Lawrence. A scholar is included among the top collaborators of Patrick J. Lawrence based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Patrick J. Lawrence. Patrick J. Lawrence is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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9 of 9 papers shown

1.

Lawrence, Patrick J., et al.. (2024). Enhancing drug and cell line representations via contrastive learning for improved anti-cancer drug prioritization. npj Precision Oncology. 8(1). 106–106. 2 indexed citations

2.

Patro, Ankita, et al.. (2024). Using Machine Learning and Multifaceted Preoperative Measures to Predict Adult Cochlear Implant Outcomes: A Prospective Pilot Study. Ear and Hearing. 46(2). 543–549. 3 indexed citations

3.

Yasuhara, Jun, Sathiyanarayanan Manivannan, Uddalak Majumdar, et al.. (2023). Novel pathogenic GATA6 variant associated with congenital heart disease, diabetes mellitus and necrotizing enterocolitis. Pediatric Research. 95(1). 146–155. 6 indexed citations

4.

Gordon, David, David Cunningham, Gloria Zender, et al.. (2022). Exome sequencing in multiplex families with left-sided cardiac defects has high yield for disease gene discovery. PLoS Genetics. 18(6). e1010236–e1010236. 15 indexed citations

5.

Lawrence, Patrick J. & Xia Ning. (2022). Improving MHC class I antigen-processing predictions using representation learning and cleavage site-specific kernels. Cell Reports Methods. 2(9). 100293–100293. 3 indexed citations

6.

Bennett, Jeffrey S., David Gordon, Uddalak Majumdar, et al.. (2021). Use of machine learning to classify high-risk variants of uncertain significance in lamin A/C cardiac disease. Heart Rhythm. 19(4). 676–685. 6 indexed citations

7.

Wu, Zhenyu, Patrick J. Lawrence, Anjun Ma, et al.. (2020). Single-Cell Techniques and Deep Learning in Predicting Drug Response. Trends in Pharmacological Sciences. 41(12). 1050–1065. 40 indexed citations

8.

Chen, Cheng, Qingmei Zhang, Bin Yu, et al.. (2020). Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier. Computers in Biology and Medicine. 123. 103899–103899. 174 indexed citations

9.

Chun, Patrick K.C., Robert C. Jones, Max Robinowitz, James E. Davia, & Patrick J. Lawrence. (1980). Coronary Ostial Stenosis in Takayasu's Arteritis. CHEST Journal. 78(2). 330–331. 35 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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