Bob Chan

626 total citations
10 papers, 463 citations indexed

About

Bob Chan is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Bob Chan has authored 10 papers receiving a total of 463 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Cancer Research and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Bob Chan's work include Gene expression and cancer classification (4 papers), Breast Cancer Treatment Studies (3 papers) and Bioinformatics and Genomic Networks (3 papers). Bob Chan is often cited by papers focused on Gene expression and cancer classification (4 papers), Breast Cancer Treatment Studies (3 papers) and Bioinformatics and Genomic Networks (3 papers). Bob Chan collaborates with scholars based in United States, Netherlands and Australia. Bob Chan's co-authors include Anthony D. Long, G. Wesley Hatfield, Pierre Baldi, Harry J. Mangalam, Dennis Kibler, Leonie Delahaye, Anke Witteveen, Christa Dreezen, Mireille H.J. Snel and Victor Kunin and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Molecular Biology and Hepatology.

In The Last Decade

Bob Chan

10 papers receiving 453 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bob Chan United States	7	306	85	84	62	33	10	463
Matthias Müller Germany	12	282 0.9×	68 0.8×	175 2.1×	63 1.0×	22 0.7×	23	520
Yongping Ma China	13	259 0.8×	69 0.8×	53 0.6×	75 1.2×	28 0.8×	31	475
Mónica Santamaría Spain	4	200 0.7×	29 0.3×	92 1.1×	48 0.8×	17 0.5×	4	335
Abid R. Mattoo United States	12	284 0.9×	33 0.4×	83 1.0×	78 1.3×	17 0.5×	20	371
Amar Joshi United Kingdom	12	316 1.0×	39 0.5×	84 1.0×	44 0.7×	12 0.4×	15	498
Junping Li China	14	170 0.6×	73 0.9×	61 0.7×	85 1.4×	14 0.4×	48	514
Annette M. Healy United States	10	351 1.1×	42 0.5×	53 0.6×	22 0.4×	23 0.7×	19	513
Petro Starokadomskyy United States	11	246 0.8×	29 0.3×	82 1.0×	56 0.9×	15 0.5×	23	434
Anthony Arnoldo Canada	12	328 1.1×	46 0.5×	61 0.7×	38 0.6×	10 0.3×	25	557
K. R. Sreekumar United States	12	303 1.0×	69 0.8×	87 1.0×	170 2.7×	16 0.5×	14	585

Countries citing papers authored by Bob Chan

Since Specialization

Citations

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

Fields of papers citing papers by Bob Chan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bob Chan

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

All Works

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10 of 10 papers shown

Jacob, Laurent, Anke Witteveen, Leonie Delahaye, et al.. (2020). Controlling technical variation amongst 6693 patient microarrays of the randomized MINDACT trial. Communications Biology. 3(1). 397–397. 5 indexed citations

Mittempergher, Lorenza, Leonie Delahaye, Anke Witteveen, et al.. (2020). Performance Characteristics of the BluePrint® Breast Cancer Diagnostic Test. Translational Oncology. 13(4). 100756–100756. 22 indexed citations

Mittempergher, Lorenza, et al.. (2020). BluePrint molecular subtyping recognizes single and dual subtype tumors with consequences for therapeutic guidance. European Journal of Cancer. 138. S106–S107. 4 indexed citations

Chiang, Chi‐Leung, Cheuk‐Wai Choi, Bob Chan, et al.. (2019). Real‐world treatment patterns and outcomes in refractory metastatic colorectal cancer. Asia-Pacific Journal of Clinical Oncology. 15(S2). 5–13. 6 indexed citations

Delahaye, Leonie, Caroline A. Drukker, Christa Dreezen, et al.. (2017). A breast cancer gene signature for indolent disease. Breast Cancer Research and Treatment. 164(2). 461–466. 21 indexed citations

Witteveen, Anke, Leonie Delahaye, Diederik Wehkamp, et al.. (2016). Equivalence of MammaPrint array types in clinical trials and diagnostics. Breast Cancer Research and Treatment. 156(2). 279–287. 36 indexed citations

Chan, Bob & Dennis Kibler. (2005). Using hexamers to predict cis-regulatory motifs in Drosophila. BMC Bioinformatics. 6(1). 262–262. 35 indexed citations

Kunin, Victor, Bob Chan, Einat Sitbon, Lithwick Gila, & Shmuel Pietrokovski. (2001). Consistency analysis of similarity between multiple alignments: prediction of protein function and fold structure from analysis of local sequence motifs. Journal of Molecular Biology. 307(3). 939–949. 29 indexed citations

Long, Anthony D., et al.. (2001). Improved Statistical Inference from DNA Microarray Data Using Analysis of Variance and A Bayesian Statistical Framework. Journal of Biological Chemistry. 276(23). 19937–19944. 301 indexed citations

10.

Malı́k, Radek, et al.. (1997). The effect of N -methyl- N ′-nitro- N -nitrosoguanidine on cultured dog gallbladder epithelial cells. Hepatology. 26(5). 1296–1302. 4 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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