Tom Jacobs

571 total citations
18 papers, 238 citations indexed

About

Tom Jacobs is a scholar working on Statistics and Probability, Computational Theory and Mathematics and Management Science and Operations Research. According to data from OpenAlex, Tom Jacobs has authored 18 papers receiving a total of 238 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Statistics and Probability, 6 papers in Computational Theory and Mathematics and 4 papers in Management Science and Operations Research. Recurrent topics in Tom Jacobs's work include Statistical Methods in Clinical Trials (8 papers), Computational Drug Discovery Methods (6 papers) and Alzheimer's disease research and treatments (4 papers). Tom Jacobs is often cited by papers focused on Statistical Methods in Clinical Trials (8 papers), Computational Drug Discovery Methods (6 papers) and Alzheimer's disease research and treatments (4 papers). Tom Jacobs collaborates with scholars based in Belgium, United States and United Kingdom. Tom Jacobs's co-authors include H.‐G. Boyen, Jan D’Haen, Linny Baeten, Bert Conings, Jean Manca, Thomas Jaki, Helena Geys, Oliver Lenz, Leen Vijgen and Thierry Verbinnen and has published in prestigious journals such as Antimicrobial Agents and Chemotherapy, Statistics in Medicine and Pharmaceutical Research.

In The Last Decade

Tom Jacobs

18 papers receiving 232 citations

Peers

Tom Jacobs

EEE

PHYSI

HEPAT

Yi‐Jie Huang China

Yanrong Wang China

Eun Young Park South Korea

Xiushan Dong China

Y. Inoue Japan

Andrew Vu United States

Liu Zhang China

Lin Ai Tai Taiwan

Isabella Sampaio Brazil

Tássia Regina de Oliveira Brazil

Yi‐Jie Huang China

Tom Jacobs

83 ×0.8

EEE

25 ×0.4

43 ×0.7

29 ×0.7

PHYSI

33 ×1.1

HEPAT

Citations per year, relative to Tom Jacobs Tom Jacobs (= 1×) peers Yi‐Jie Huang

Countries citing papers authored by Tom Jacobs

Since Specialization

Citations

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

Fields of papers citing papers by Tom Jacobs

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Jacobs. 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 Tom Jacobs. The network helps show where Tom Jacobs may publish in the future.

Co-authorship network of co-authors of Tom Jacobs

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Jacobs. A scholar is included among the top collaborators of Tom Jacobs 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 Tom Jacobs. Tom Jacobs 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:

18 of 18 papers shown

Geys, Helena, et al.. (2020). Methods for Non-Compartmental Pharmacokinetic Analysis With Observations Below the Limit of Quantification. Statistics in Biopharmaceutical Research. 13(1). 59–70. 11 indexed citations

Jacobs, Tom, et al.. (2020). Bayesian pooling versus sequential integration of small preclinical trials: a comparison within linear and nonlinear modeling frameworks. Journal of Biopharmaceutical Statistics. 31(1). 25–36. 1 indexed citations

Jacobs, Tom, Helena Geys, Thomas Jaki, et al.. (2019). Bayesian sequential integration within a preclinical pharmacokinetic and pharmacodynamic modeling framework: Lessons learned. Pharmaceutical Statistics. 18(4). 486–506. 4 indexed citations

Galpern, Wendy R., Marc Mercken, Kristof Van Kolen, et al.. (2019). P1‐052: A SINGLE ASCENDING DOSE STUDY TO EVALUATE THE SAFETY, TOLERABILITY, PHARMACOKINETICS, AND PHARMACODYNAMICS OF THE ANTI‐PHOSPHO‐TAU ANTIBODY JNJ‐63733657 IN HEALTHY SUBJECTS. Alzheimer s & Dementia. 15(7S_Part_5). 24 indexed citations

Jaki, Thomas, A. Gordon, Luc Bijnens, et al.. (2018). A proposal for a new PhD level curriculum on quantitative methods for drug development. Pharmaceutical Statistics. 17(5). 593–606. 4 indexed citations

Geys, Helena, et al.. (2018). Optimal Designs for Non-Compartmental Analysis of Pharmacokinetic Studies. Statistics in Biopharmaceutical Research. 10(4). 255–263. 3 indexed citations

Jacobs, Tom, et al.. (2018). A Bayesian K‐PD model for synergy: A case study. Pharmaceutical Statistics. 17(6). 674–684. 3 indexed citations

Ito, Hisanori, Hidekuni Yamakawa, Kouhei Nishitomi, et al.. (2017). [P1–075]: PRECLINICAL MULTI‐SPECIES PHARMACOKINETIC/PHARMACODYNAMIC ANALYSIS OF THE ORAL BACE INHIBITOR JNJ‐54861911. Alzheimer s & Dementia. 13(7S_Part_5). 2 indexed citations

Geys, Helena, et al.. (2017). Comparing sampling methods for pharmacokinetic studies using model averaged derived parameters. Statistics in Medicine. 36(27). 4301–4315. 1 indexed citations

10.

Borghys, Herman, Bianca Van Broeck, Tom Jacobs, et al.. (2016). Young to Middle-Aged Dogs with High Amyloid-β Levels in Cerebrospinal Fluid are Impaired on Learning in Standard Cognition tests. Journal of Alzheimer s Disease. 56(2). 763–774. 23 indexed citations

11.

Verbinnen, Thierry, Bart Fevery, Leen Vijgen, et al.. (2015). In Vitro Activity of Simeprevir against Hepatitis C Virus Genotype 1 Clinical Isolates and Its Correlation with NS3 Sequence and Site-Directed Mutants. Antimicrobial Agents and Chemotherapy. 59(12). 7548–7557. 20 indexed citations

12.

Conings, Bert, Linny Baeten, Tom Jacobs, et al.. (2014). An easy-to-fabricate low-temperature TiO2 electron collection layer for high efficiency planar heterojunction perovskite solar cells. APL Materials. 2(8). 107 indexed citations

13.

Borghys, Herman, Tom Jacobs, Bianca Van Broeck, et al.. (2013). Comparison of Two Different Methods for Measurement of Amyloid-β Peptides in Cerebrospinal Fluid after BACE1 Inhibition in a Dog Model. Journal of Alzheimer s Disease. 38(1). 39–48. 7 indexed citations

14.

Verbinnen, Thierry, Tom Jacobs, Leen Vijgen, et al.. (2012). Replication capacity of minority variants in viral populations can affect the assessment of resistance in HCV chimeric replicon phenotyping assays. Journal of Antimicrobial Chemotherapy. 67(10). 2327–2337. 11 indexed citations

15.

Loock, Marnix Van, Anneleen Hombrouck, Tom Jacobs, et al.. (2012). Reporter gene expression from LTR-circles as tool to identify HIV-1 integrase inhibitors. Journal of Virological Methods. 187(2). 238–247. 5 indexed citations

16.

Jacobs, Tom, Roel Straetemans, Geert Molenberghs, J. Adriaan Bouwknecht, & Luc Bijnens. (2010). A Latent Pharmacokinetic Time Profile to Model Dose-Response Survival Data. Journal of Biopharmaceutical Statistics. 20(4). 759–767. 4 indexed citations

17.

Jacobs, Tom, Filip De Ridder, Sarah Rusch, et al.. (2008). Including Information on the Therapeutic Window in Bioequivalence Acceptance. Pharmaceutical Research. 25(11). 2628–2638. 2 indexed citations

18.

Jacobs, Tom, Stefaan Rossenu, Adrian Dunne, et al.. (2008). Combined Models for Data from In Vitro–In Vivo Correlation Experiments. Journal of Biopharmaceutical Statistics. 18(6). 1197–1211. 6 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