Daniel M. Lowe

2.1k total citations
10 papers, 867 citations indexed

About

Daniel M. Lowe is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Daniel M. Lowe has authored 10 papers receiving a total of 867 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Computational Theory and Mathematics and 3 papers in Artificial Intelligence. Recurrent topics in Daniel M. Lowe's work include Computational Drug Discovery Methods (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Machine Learning in Materials Science (3 papers). Daniel M. Lowe is often cited by papers focused on Computational Drug Discovery Methods (6 papers), Biomedical Text Mining and Ontologies (5 papers) and Machine Learning in Materials Science (3 papers). Daniel M. Lowe collaborates with scholars based in United Kingdom, Germany and Switzerland. Daniel M. Lowe's co-authors include Roger A. Sayle, Nadine Schneider, Gregory A. Landrum, Michael A. Tarselli, Robert C. Glen, Peter Murray‐Rust, Peter Corbett, Igor V. Tetko, Antony Williams and Gianpaolo Bravi and has published in prestigious journals such as PLoS ONE, Journal of Medicinal Chemistry and Bioorganic & Medicinal Chemistry.

In The Last Decade

Daniel M. Lowe

10 papers receiving 838 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel M. Lowe United Kingdom	8	368	365	280	259	121	10	867
Wiktor Beker Poland	14	353 1.0×	382 1.0×	201 0.7×	578 2.2×	54 0.4×	28	1.1k
Rafał Roszak Poland	12	281 0.8×	291 0.8×	173 0.6×	439 1.7×	45 0.4×	27	928
Timur Madzhidov Russia	18	524 1.4×	818 2.2×	168 0.6×	662 2.6×	75 0.6×	60	1.2k
Tomasz Klucznik South Korea	10	454 1.2×	574 1.6×	144 0.5×	624 2.4×	76 0.6×	15	1.1k
Jesús G. Estrada United States	4	178 0.5×	324 0.9×	252 0.9×	488 1.9×	46 0.4×	4	882
Ramil Nugmanov Russia	16	247 0.7×	416 1.1×	133 0.5×	433 1.7×	56 0.5×	45	663
Timur Gimadiev Russia	15	163 0.4×	319 0.9×	145 0.5×	318 1.2×	38 0.3×	31	561
Agnieszka Wołos Poland	9	224 0.6×	208 0.6×	91 0.3×	259 1.0×	37 0.3×	16	601
Piotr Dittwald Poland	15	632 1.7×	681 1.9×	145 0.5×	722 2.8×	90 0.7×	25	1.4k
Karol Molga Poland	15	573 1.6×	752 2.1×	187 0.7×	788 3.0×	96 0.8×	25	1.4k

Countries citing papers authored by Daniel M. Lowe

Since Specialization

Citations

This map shows the geographic impact of Daniel M. Lowe'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 Daniel M. Lowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel M. Lowe more than expected).

Fields of papers citing papers by Daniel M. Lowe

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel M. Lowe. 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 Daniel M. Lowe. The network helps show where Daniel M. Lowe may publish in the future.

Co-authorship network of co-authors of Daniel M. Lowe

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel M. Lowe. A scholar is included among the top collaborators of Daniel M. Lowe 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 Daniel M. Lowe. Daniel M. Lowe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

10 of 10 papers shown

Lowe, Daniel M. & John E. Mayfield. (2020). Extraction of Reactions from Patents using Grammars.. CLEF (Working Notes). 4 indexed citations

Tetko, Igor V., Daniel M. Lowe, & Antony Williams. (2016). The development of models to predict melting and pyrolysis point data associated with several hundred thousand compounds mined from PATENTS. Journal of Cheminformatics. 8(1). 2–2. 65 indexed citations

Lowe, Daniel M., Noel M. O’Boyle, & Roger A. Sayle. (2016). Efficient chemical-disease identification and relationship extraction using Wikipedia to improve recall. Database. 2016. baw039–baw039. 18 indexed citations

Schneider, Nadine, Daniel M. Lowe, Roger A. Sayle, Michael A. Tarselli, & Gregory A. Landrum. (2016). Big Data from Pharmaceutical Patents: A Computational Analysis of Medicinal Chemists’ Bread and Butter. Journal of Medicinal Chemistry. 59(9). 4385–4402. 328 indexed citations

Lowe, Daniel M. & Roger A. Sayle. (2015). LeadMine: a grammar and dictionary driven approach to entity recognition. Journal of Cheminformatics. 7(S1). S5–S5. 49 indexed citations

Akhondi, Saber A., Alexander Klenner, Christian Tyrchan, et al.. (2014). Annotated Chemical Patent Corpus: A Gold Standard for Text Mining. PLoS ONE. 9(9). e107477–e107477. 38 indexed citations

Schneider, Nadine, Daniel M. Lowe, Roger A. Sayle, & Gregory A. Landrum. (2014). Development of a Novel Fingerprint for Chemical Reactions and Its Application to Large-Scale Reaction Classification and Similarity. Journal of Chemical Information and Modeling. 55(1). 39–53. 128 indexed citations

Horan, Ben, et al.. (2011). Virtual haptic cell model for operator training. Deakin Research Online (Deakin University). 1–5. 7 indexed citations

Lowe, Daniel M., Peter Corbett, Peter Murray‐Rust, & Robert C. Glen. (2011). Chemical Name to Structure: OPSIN, an Open Source Solution. Journal of Chemical Information and Modeling. 51(3). 739–753. 152 indexed citations

10.

Gleeson, M. Paul, Gianpaolo Bravi, Sandeep Modi, & Daniel M. Lowe. (2009). ADMET rules of thumb II: A comparison of the effects of common substituents on a range of ADMET parameters. Bioorganic & Medicinal Chemistry. 17(16). 5906–5919. 78 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.

Explore authors with similar magnitude of impact