Bie Verbist

1.5k total citations · 1 hit paper
26 papers, 1.0k citations indexed

About

Bie Verbist is a scholar working on Molecular Biology, Computational Theory and Mathematics and Organic Chemistry. According to data from OpenAlex, Bie Verbist has authored 26 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 7 papers in Computational Theory and Mathematics and 6 papers in Organic Chemistry. Recurrent topics in Bie Verbist's work include Computational Drug Discovery Methods (7 papers), Synthesis and Reactions of Organic Compounds (5 papers) and Bacteriophages and microbial interactions (4 papers). Bie Verbist is often cited by papers focused on Computational Drug Discovery Methods (7 papers), Synthesis and Reactions of Organic Compounds (5 papers) and Bacteriophages and microbial interactions (4 papers). Bie Verbist collaborates with scholars based in Belgium, United States and Australia. Bie Verbist's co-authors include Inger S. Nijhof, Tuna Mutis, Tahamtan Ahmadi, Brendan M. Weiss, Niels W.C.J. van de Donk, Jakub Krejcik, Torben Plesner, Jaime Bald, Tineke Casneuf and A. Kate Sasser and has published in prestigious journals such as Blood, Bioinformatics and Cancer Research.

In The Last Decade

Bie Verbist

25 papers receiving 989 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Daratumumab depletes CD38+ immune regulatory cells, promotes T-cell expansion, and skews T-cell repertoire in multiple myeloma

2016 649 citations Tineke Casneuf, Bie Verbist et al. Blood profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bie Verbist Belgium	10	437	416	369	229	109	26	1.0k
Sondra Goehle United States	20	418 1.0×	627 1.5×	296 0.8×	320 1.4×	99 0.9×	30	1.6k
Antoine Désilets Canada	18	173 0.4×	303 0.7×	120 0.3×	87 0.4×	105 1.0×	35	768
Jing An United States	20	115 0.3×	638 1.5×	600 1.6×	479 2.1×	37 0.3×	61	1.2k
Leonid Karawajew Germany	30	828 1.9×	1.1k 2.7×	573 1.6×	499 2.2×	180 1.7×	82	2.4k
Anneliese O. Speak United Kingdom	21	178 0.4×	611 1.5×	361 1.0×	1.4k 6.2×	36 0.3×	40	2.2k
Concetta Pietropaolo Italy	17	170 0.4×	498 1.2×	93 0.3×	245 1.1×	81 0.7×	26	1.0k
Wouter Pos Netherlands	13	194 0.4×	306 0.7×	135 0.4×	597 2.6×	131 1.2×	18	901
Stéphanie McArdle United Kingdom	22	93 0.2×	547 1.3×	399 1.1×	523 2.3×	97 0.9×	64	1.3k
Jani Saarela Finland	19	107 0.2×	583 1.4×	163 0.4×	113 0.5×	61 0.6×	45	999
A Goldin United States	19	143 0.3×	478 1.1×	454 1.2×	258 1.1×	68 0.6×	114	1.3k

Countries citing papers authored by Bie Verbist

Since Specialization

Citations

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

Fields of papers citing papers by Bie Verbist

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bie Verbist

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

All Works

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20 of 20 papers shown

Verbist, Bie, et al.. (2024). Synergy detection: A practical guide to statistical assessment of potential drug combinations. Pharmaceutical Statistics. 24(1). e2383–e2383.

Verbist, Bie, et al.. (2023). Automated quality control tool for high-content imaging data by building 2D prediction intervals on reference biosignatures. SLAS DISCOVERY. 28(3). 111–117. 2 indexed citations

Kwon, Min Chul, Tinne Verhulst, Bie Verbist, et al.. (2023). Preclinical Efficacy of the Menin-KMT2A Inhibitor JNJ-75276617 in Combination with Venetoclax and Azacitidine in AML. Blood. 142(Supplement 1). 4167–4167. 2 indexed citations

Lebrun, Pierre, et al.. (2020). Controlling the Reproducibility of AC50 Estimation during Compound Profiling through Bayesian β-Expectation Tolerance Intervals. SLAS DISCOVERY. 25(9). 1009–1017. 3 indexed citations

Verbist, Bie, et al.. (2019). Analyzing magnetic bead QuantiGene® Plex 2.0 gene expression data in high throughput mode using QGprofiler. BMC Bioinformatics. 20(1). 378–378. 6 indexed citations

Borght, Koen Van der, et al.. (2017). BIGL: Biochemically Intuitive Generalized Loewe null model for prediction of the expected combined effect compatible with partial agonism and antagonism. Scientific Reports. 7(1). 17935–17935. 18 indexed citations

Casneuf, Tineke, Xiuping Xu, Amy Axel, et al.. (2016). PHARMACODYNAMIC RELATIONSHIP BETWEEN NATURAL KILLER CELLS AND DARATUMUMAB EXPOSURE IN RELAPSED/REFRACTORY MULTIPLE MYELOMA. Pure Amsterdam UMC. 101. 87–88. 7 indexed citations

Mattiello, Federico, Bie Verbist, Karoline Faust, et al.. (2016). A web application for sample size and power calculation in case-control microbiome studies. Bioinformatics. 32(13). 2038–2040. 56 indexed citations

Kasim, Adetayo, et al.. (2016). A joint modeling approach for uncovering associations between gene expression, bioactivity and chemical structure in early drug discovery to guide lead selection and genomic biomarker development. Statistical Applications in Genetics and Molecular Biology. 15(4). 291–304. 2 indexed citations

10.

Thys, Kim, Peter Verhasselt, Joke Reumers, et al.. (2015). Performance assessment of the Illumina massively parallel sequencing platform for deep sequencing analysis of viral minority variants. Journal of Virological Methods. 221. 29–38. 24 indexed citations

11.

Borght, Koen Van der, Kim Thys, Lieven Clement, et al.. (2015). QQ-SNV: single nucleotide variant detection at low frequency by comparing the quality quantiles. BMC Bioinformatics. 16(1). 379–379. 2 indexed citations

12.

Verbist, Bie, Lieven Clement, Joke Reumers, et al.. (2015). ViVaMBC: estimating viral sequence variation in complex populations from illumina deep-sequencing data using model-based clustering. BMC Bioinformatics. 16(1). 59–59. 9 indexed citations

13.

Verbist, Bie, Günter Klambauer, Willem Talloen, et al.. (2015). Using transcriptomics to guide lead optimization in drug discovery projects: Lessons learned from the QSTAR project. Drug Discovery Today. 20(5). 505–513. 63 indexed citations

14.

Verbist, Bie, Geert R. Verheyen, Marjolein Crabbe, et al.. (2015). Integrating High-Dimensional Transcriptomics and Image Analysis Tools into Early Safety Screening: Proof of Concept for a New Early Drug Development Strategy. Chemical Research in Toxicology. 28(10). 1914–1925. 7 indexed citations

15.

Verbist, Bie, Kim Thys, Joke Reumers, et al.. (2014). VirVarSeq: a low-frequency virus variant detection pipeline for Illumina sequencing using adaptive base-calling accuracy filtering. Bioinformatics. 31(1). 94–101. 36 indexed citations

16.

Gijsen, Harrie J. M., Bie Verbist, Marjoleen Nijsen, et al.. (2011). 5-Sulfonyl-benzimidazoles as selective CB2 agonists-Part 2. Bioorganic & Medicinal Chemistry Letters. 22(1). 547–552. 26 indexed citations

17.

Verbist, Bie, et al.. (2008). 5-Sulfonyl-benzimidazoles as selective CB2 agonists. Bioorganic & Medicinal Chemistry Letters. 18(8). 2574–2579. 25 indexed citations

18.

Verbist, Bie, Wim M. De Borggraeve, Suzanne Toppet, Frans Compernolle, & Georges J. Hoornaert. (2005). Development of New Amino(oxo)piperidinecarboxylate Scaffolds and Their Evaluation as ‐Turn Mimics. European Journal of Organic Chemistry. 2005(14). 2941–2950. 9 indexed citations

19.

Verbist, Bie, et al.. (2004). Acid catalysed methanolysis of 2,5-diazabicyclo[2.2.2]octane-3,6-diones: scope and limitations. Tetrahedron Letters. 45(22). 4371–4374. 6 indexed citations

20.

Borggraeve, Wim M. De, Frederik Rombouts, Bie Verbist, Erik V. Van der Eycken, & Georges J. Hoornaert. (2002). Stereoselective intramolecular Diels–Alder reactions of 3-alkenyl(oxy)-2(1H)-pyrazinones. Tetrahedron Letters. 43(3). 447–449. 11 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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