Mark Velleca

1.3k total citations
18 papers, 1.1k citations indexed

About

Mark Velleca is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Mark Velleca has authored 18 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 4 papers in Oncology and 2 papers in Hematology. Recurrent topics in Mark Velleca's work include Cancer Treatment and Pharmacology (3 papers), RNA and protein synthesis mechanisms (3 papers) and Cellular transport and secretion (2 papers). Mark Velleca is often cited by papers focused on Cancer Treatment and Pharmacology (3 papers), RNA and protein synthesis mechanisms (3 papers) and Cellular transport and secretion (2 papers). Mark Velleca collaborates with scholars based in United States, India and United Kingdom. Mark Velleca's co-authors include Scott Roberts, Jason Christiansen, Velizar T. Tchernev, Minjuan Wang, Stephen F. Kingsmore, Zhimin Zhou, Qin Fu, Brian G. Grimwade, Barry Schweitzer and Kevan M. Shokat and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Cell Biology and Nature Biotechnology.

In The Last Decade

Mark Velleca

18 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Velleca United States 10 937 225 175 125 100 18 1.1k
Charlotta Olsson Sweden 6 1.0k 1.1× 294 1.3× 109 0.6× 64 0.5× 141 1.4× 6 1.3k
Kenji Tatematsu Japan 20 671 0.7× 116 0.5× 80 0.5× 113 0.9× 125 1.3× 40 970
Giuseppe A. Papalia United States 12 494 0.5× 115 0.5× 157 0.9× 77 0.6× 58 0.6× 14 721
Godfrey Amphlett United States 18 929 1.0× 64 0.3× 494 2.8× 98 0.8× 72 0.7× 21 2.0k
Kristmundur Sigmundsson Sweden 17 512 0.5× 62 0.3× 140 0.8× 118 0.9× 65 0.7× 26 1.0k
Tatsuya Inui Japan 15 547 0.6× 58 0.3× 75 0.4× 59 0.5× 176 1.8× 34 816
Tatiana Coelho‐Sampaio Brazil 18 424 0.5× 111 0.5× 67 0.4× 61 0.5× 163 1.6× 42 876
Veerle De Corte Belgium 16 634 0.7× 56 0.2× 74 0.4× 73 0.6× 486 4.9× 24 1.0k
Uyen Nguyen United States 17 1.2k 1.2× 51 0.2× 164 0.9× 49 0.4× 164 1.6× 29 1.4k
Thomas G. Easton United States 10 435 0.5× 47 0.2× 99 0.6× 153 1.2× 132 1.3× 10 907

Countries citing papers authored by Mark Velleca

Since Specialization
Citations

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

Fields of papers citing papers by Mark Velleca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Velleca

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

All Works

18 of 18 papers shown
1.
2.
Gordon, Michael S., et al.. (2010). 400 Phase I study of JI-101, a novel oral tyrosine kinase inhibitor that selectively targets EphB4, VEGFR2, and PDGFRβ. European Journal of Cancer Supplements. 8(7). 127–127. 2 indexed citations
3.
Sharma, Santosh Kumar, Ramesh Mullangi, Deepa Shankar, et al.. (2010). 196 PK/PD models using a selective Ephrin B4 inhibitor JI-101 alone and in combination with other targeted agents and chemotherapy: Results of preclinical and ex-vivo studies. European Journal of Cancer Supplements. 8(7). 66–66. 2 indexed citations
4.
Velleca, Mark, Sunil Sharma, Michael S. Gordon, et al.. (2010). Abstract 17: Preclinical and phase 1 trial results of JI-101, a novel, oral tyrosine kinase inhibitor that selectively targets VEGFR2, EphB4, and PDGFRβ. Cancer Research. 70(8_Supplement). 17–17. 3 indexed citations
5.
Velleca, Mark, David R. Brittelli, Lisa Elkin, et al.. (2009). Abstract B11: Preclinical and preliminary phase 1 trial results of JI-101: A novel, oral tyrosine kinase inhibitor that selectively targets VEGFR2, EphB4, and PDGFR. Molecular Cancer Therapeutics. 8(12_Supplement). B11–B11. 5 indexed citations
6.
Jiang, Shan, Kevin Currie, Xiaobing Qian, et al.. (2007). Chemical Genetic Transcriptional Fingerprinting for Selectivity Profiling of Kinase Inhibitors. Assay and Drug Development Technologies. 5(1). 49–64. 2 indexed citations
7.
Heck, Susanne, Xiaobing Qian, & Mark Velleca. (2004). Genetically Engineered Mouse Models for Drug Discovery: New Chemical Genetic Approaches. Current Drug Discovery Technologies. 1(1). 13–26. 11 indexed citations
8.
Benton, Benjamin K., Christian Rommel, Mark Velleca, & Christian Pasquali. (2004). Mining for Protein Kinase Substrates: Integration of Biochemistry, Genetics and Proteomics. Current Proteomics. 1(2). 83–102. 1 indexed citations
9.
Shokat, Kevan M. & Mark Velleca. (2002). Novel chemical genetic approaches to the discovery of signal transduction inhibitors. Drug Discovery Today. 7(16). 872–879. 62 indexed citations
10.
Schweitzer, Barry, Scott Roberts, Brian G. Grimwade, et al.. (2002). Multiplexed protein profiling on microarrays by rolling-circle amplification. Nature Biotechnology. 20(4). 359–365. 461 indexed citations
11.
Snyder, Edward L., Lynn O’Donnell, Thomas J. Dengler, et al.. (2001). Ex vivo evaluation of PBMNCs collected with a new cell separator. Transfusion. 41(7). 940–949. 10 indexed citations
12.
Gatti, Evelina, Mark Velleca, Barbara Biedermann, et al.. (2000). Large-Scale Culture and Selective Maturation of Human Langerhans Cells from Granulocyte Colony-Stimulating Factor-Mobilized CD34+ Progenitors. The Journal of Immunology. 164(7). 3600–3607. 89 indexed citations
13.
Chu, Gerald C., Mark Velleca, & John P. Merlie. (1995). Synapse-specific gene expression. 6(3). 175–183. 7 indexed citations
14.
Hu, C., Stephen C. Pang, Xiuying Kong, Mark Velleca, & John C. Lawrence. (1994). Molecular cloning and tissue distribution of PHAS-I, an intracellular target for insulin and growth factors.. Proceedings of the National Academy of Sciences. 91(9). 3730–3734. 119 indexed citations
15.
Velleca, Mark, Mia Wallace, & John P. Merlie. (1994). A Novel Synapse-Associated Noncoding RNA. Molecular and Cellular Biology. 14(11). 7095–7104. 15 indexed citations
16.
Velleca, Mark, Mia Wallace, & John P. Merlie. (1994). A novel synapse-associated noncoding RNA.. Molecular and Cellular Biology. 14(11). 7095–7104. 47 indexed citations
17.
Ausoni, Simonetta, Paolo Moretti, Luisa Gorza, et al.. (1993). Type 2X-myosin heavy chain is coded by a muscle fiber type-specific and developmentally regulated gene.. The Journal of Cell Biology. 123(4). 823–835. 194 indexed citations
18.
Velleca, Mark, et al.. (1989). Molecular cloning and sequence analysis of the Chlamydomonas gene coding for radial spoke protein 3: flagellar mutation pf-14 is an ochre allele.. The Journal of Cell Biology. 109(1). 235–245. 85 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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