Brian Van Ness

7.8k total citations
83 papers, 3.7k citations indexed

About

Brian Van Ness is a scholar working on Hematology, Molecular Biology and Oncology. According to data from OpenAlex, Brian Van Ness has authored 83 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 49 papers in Hematology, 45 papers in Molecular Biology and 23 papers in Oncology. Recurrent topics in Brian Van Ness's work include Multiple Myeloma Research and Treatments (47 papers), T-cell and B-cell Immunology (16 papers) and Monoclonal and Polyclonal Antibodies Research (15 papers). Brian Van Ness is often cited by papers focused on Multiple Myeloma Research and Treatments (47 papers), T-cell and B-cell Immunology (16 papers) and Monoclonal and Polyclonal Antibodies Research (15 papers). Brian Van Ness collaborates with scholars based in United States, France and United Kingdom. Brian Van Ness's co-authors include Daniel D. Billadeau, Martin M. Oken, Philip R. Greipp, Robert A. Kyle, Neil E. Kay, Patricia T. Greipp, Rafaël Fonseca, David Harrington, Traci Leong and Kimberly J. Henderson and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Journal of Clinical Investigation.

In The Last Decade

Brian Van Ness

83 papers receiving 3.7k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Brian Van Ness 2.4k 2.2k 1.3k 581 569 83 3.7k
A. Keith Stewart 1.8k 0.8× 2.4k 1.1× 1.4k 1.1× 463 0.8× 549 1.0× 100 3.9k
Michael H. Tomasson 1.8k 0.8× 1.6k 0.7× 1.3k 1.0× 659 1.1× 486 0.9× 116 3.5k
Nelly Robillard 1.7k 0.7× 1.6k 0.7× 1.2k 1.0× 641 1.1× 1.1k 1.9× 94 3.8k
Carla S. Wilson 2.8k 1.2× 2.3k 1.0× 1.7k 1.3× 736 1.3× 466 0.8× 37 4.3k
Hetty E. Carraway 1.4k 0.6× 1.7k 0.8× 1.1k 0.9× 815 1.4× 488 0.9× 212 3.6k
Bruno Paiva 3.4k 1.4× 2.6k 1.2× 1.9k 1.6× 829 1.4× 804 1.4× 157 4.7k
Catherine Pellat‐Deceunynck 1.5k 0.6× 1.9k 0.9× 1.2k 1.0× 523 0.9× 1.3k 2.2× 98 3.7k
Jesús G. Berdeja 2.9k 1.2× 3.1k 1.4× 3.0k 2.4× 536 0.9× 717 1.3× 257 5.0k
Geoffrey L. Uy 2.9k 1.2× 1.6k 0.7× 1.5k 1.2× 536 0.9× 900 1.6× 214 4.6k
Hareth Nahi 2.0k 0.8× 1.6k 0.7× 1.5k 1.2× 437 0.8× 559 1.0× 143 3.0k

Countries citing papers authored by Brian Van Ness

Since Specialization
Citations

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

Fields of papers citing papers by Brian Van Ness

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Brian Van Ness. 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 Brian Van Ness. The network helps show where Brian Van Ness may publish in the future.

Co-authorship network of co-authors of Brian Van Ness

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

All Works

20 of 20 papers shown
1.
Ferguson, Ian, Yu-Hsiu T. Lin, Hao Shao, et al.. (2022). Allosteric HSP70 inhibitors perturb mitochondrial proteostasis and overcome proteasome inhibitor resistance in multiple myeloma. Cell chemical biology. 29(8). 1288–1302.e7. 17 indexed citations
2.
Fang, Gang, Wen Wang, Hamed Heydari, et al.. (2019). Discovering genetic interactions bridging pathways in genome-wide association studies. Nature Communications. 10(1). 4274–4274. 49 indexed citations
3.
4.
Mitra, Amit, Ujjal Kumar Mukherjee, Jin Sung Jang, et al.. (2017). A gene expression signature distinguishes innate response and resistance to proteasome inhibitors in multiple myeloma. Blood Cancer Journal. 7(6). e581–e581. 33 indexed citations
5.
Petersen, Gloria M. & Brian Van Ness. (2015). Returning a Research Participant's Genomic Results to Relatives: Perspectives from Managers of Two Distinct Research Biobanks. The Journal of Law Medicine & Ethics. 43(3). 523–528. 4 indexed citations
6.
Andreotti, Gabriella, Michael Katz, Antje Hoering, et al.. (2015). Risk of multiple myeloma in a case–spouse study. Leukemia & lymphoma. 57(6). 1450–1459. 7 indexed citations
7.
Ness, Brian Van, et al.. (2012). Return of individual research results and incidental findings in the clinical trials cooperative group setting. Genetics in Medicine. 14(4). 411–416. 11 indexed citations
8.
Kyle, Robert A., Traci Leong, Shuli Li, et al.. (2006). Complete response in multiple myeloma. Cancer. 106(9). 1958–1966. 40 indexed citations
9.
Fonseca, Rafaël, David Harrington, Martin M. Oken, et al.. (2002). Biological and prognostic significance of interphase fluorescence in situ hybridization detection of chromosome 13 abnormalities (delta13) in multiple myeloma: an eastern cooperative oncology group study.. PubMed. 62(3). 715–20. 139 indexed citations
10.
11.
Ness, Brian Van, et al.. (2001). The bone marrow stromal microenvironment influences myeloma therapeutic response in vitro. Leukemia. 15(2). 264–271. 47 indexed citations
12.
Liu, Xiangdong, Michael A. Linden, & Brian Van Ness. (2000). Induced κ Receptor Editing Shows No Allelic Preference in a Mouse Pre-B Cell Line. The Journal of Immunology. 165(12). 7058–7063. 6 indexed citations
13.
Liu, Xiangdong, et al.. (1999). Developmental Regulation of the κ Locus Involves Both Positive and Negative Sequence Elements in the 3′ Enhancer That Affect Synergy with the Intron Enhancer. Journal of Biological Chemistry. 274(6). 3285–3293. 19 indexed citations
14.
Kay, Neil E., Traci Leong, Nancy D. Bone, et al.. (1998). T‐helper phenotypes in the blood of myeloma patients on ECOG phase III trials E9486/E3A93. British Journal of Haematology. 100(3). 459–463. 23 indexed citations
15.
Billadeau, Daniel D., Patricia T. Greipp, Gregory Ahmann, T.E. Witzig, & Brian Van Ness. (1995). Detection of B-Cells Clonally Related to the Tumor Population in Multiple Myeloma and MGUS. Current topics in microbiology and immunology. 194. 9–16. 8 indexed citations
16.
Billadeau, Daniel D., Gregory Ahmann, Patricia T. Greipp, & Brian Van Ness. (1993). The bone marrow of multiple myeloma patients contains B cell populations at different stages of differentiation that are clonally related to the malignant plasma cell.. The Journal of Experimental Medicine. 178(3). 1023–1031. 202 indexed citations
17.
18.
LeBien, Tucker W., et al.. (1991). Induced rearrangement of kappa genes in the BLIN-1 human pre-B cell line correlates with germline J-C kappa and V kappa transcription.. The Journal of Experimental Medicine. 173(3). 639–645. 44 indexed citations
19.
Nelms, Keats & Brian Van Ness. (1990). Identification of an Octamer-Binding Site in the Human Kappa Light-Chain Enhancer. Molecular and Cellular Biology. 10(7). 3843–3846. 9 indexed citations
20.
Mathur, Ambika, Brian Van Ness, & Richard G. Lynch. (1987). Fc-Specific Suppressor T Cells. Advances in experimental medicine and biology. 216A. 69–74. 1 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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