Steven Novick

1.2k total citations
52 papers, 753 citations indexed

About

Steven Novick is a scholar working on Statistics and Probability, Molecular Biology and Management Science and Operations Research. According to data from OpenAlex, Steven Novick has authored 52 papers receiving a total of 753 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Statistics and Probability, 14 papers in Molecular Biology and 13 papers in Management Science and Operations Research. Recurrent topics in Steven Novick's work include Statistical Methods in Clinical Trials (21 papers), Optimal Experimental Design Methods (13 papers) and Pesticide Residue Analysis and Safety (8 papers). Steven Novick is often cited by papers focused on Statistical Methods in Clinical Trials (21 papers), Optimal Experimental Design Methods (13 papers) and Pesticide Residue Analysis and Safety (8 papers). Steven Novick collaborates with scholars based in United States, Australia and United Kingdom. Steven Novick's co-authors include Arthur Christopoulos, Vanessa Muniz‐Medina, Christian Watson, Terry Kenakin, John J. Peterson, Harry Yang, Leonard A. Stefanski, Claire Townsend, Brian T. Donovan and Harry Yang and has published in prestigious journals such as Journal of the American Statistical Association, Blood and Bioinformatics.

In The Last Decade

Steven Novick

47 papers receiving 728 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Steven Novick United States 13 459 263 101 85 71 52 753
Ben G. Small United Kingdom 14 331 0.7× 92 0.3× 18 0.2× 74 0.9× 41 0.6× 19 585
Xiao Zhu China 16 438 1.0× 183 0.7× 16 0.2× 139 1.6× 120 1.7× 76 1000
Oleg Demin Russia 19 764 1.7× 57 0.2× 43 0.4× 148 1.7× 62 0.9× 49 1.1k
Joseph J. DeGeorge United States 17 325 0.7× 142 0.5× 36 0.4× 64 0.8× 110 1.5× 40 821
Edgar Schuck United States 18 198 0.4× 41 0.2× 37 0.4× 109 1.3× 148 2.1× 42 760
Chayan Acharya United States 11 330 0.7× 98 0.4× 14 0.1× 146 1.7× 107 1.5× 16 611
Meijian Zhou United States 17 305 0.7× 66 0.3× 39 0.4× 52 0.6× 60 0.8× 27 710
Scott Fountain United States 12 442 1.0× 45 0.2× 61 0.6× 42 0.5× 78 1.1× 18 1.0k
Lisa A. Shipley United States 12 193 0.4× 81 0.3× 30 0.3× 37 0.4× 138 1.9× 22 581
Natalia Khuri United States 11 312 0.7× 33 0.1× 9 0.1× 89 1.0× 236 3.3× 32 685

Countries citing papers authored by Steven Novick

Since Specialization
Citations

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

Fields of papers citing papers by Steven Novick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Steven Novick

This figure shows the co-authorship network connecting the top 25 collaborators of Steven Novick. A scholar is included among the top collaborators of Steven Novick 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 Steven Novick. Steven Novick 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.
Jones, Jonathan Spencer, Xiang Zhang, Peter Könings, et al.. (2024). Quality by Design for Preclinical In Vitro Assay Development. Pharmaceutical Statistics. 24(1). e2430–e2430. 1 indexed citations
2.
Wang, Junmin & Steven Novick. (2024). Peptide set test: a peptide-centric strategy to infer differentially expressed proteins. Bioinformatics. 40(5). 1 indexed citations
3.
Leong, Hui Sun, Tianhui Zhang, Adam Corrigan, et al.. (2024). Hit screening with multivariate robust outlier detection. PLoS ONE. 19(9). e0310433–e0310433.
4.
Novick, Steven, et al.. (2024). Non-constant mean relative potency for antibody-dependent cellular cytotoxicity assays. Journal of Biopharmaceutical Statistics. 1–12. 1 indexed citations
5.
Wang, Junmin & Steven Novick. (2023). DOSE-L1000: unveiling the intricate landscape of compound-induced transcriptional changes. Bioinformatics. 39(11). 4 indexed citations
6.
Phillips, Benjamin, et al.. (2023). Whole-cage randomization for animal studies with unequal cage or group sizes. Journal of Biopharmaceutical Statistics. 1–11. 1 indexed citations
7.
Skarbnik, Alan P, Luke Mountjoy, Zaw Myint, et al.. (2022). Trial in Progress: First Report of the Phase 1/2 Study of the Safety and Efficacy of CPO107, a Bispecific Agent Targeting CD20/CD47 in CD20 Expressing Non-Hodgkin Lymphoma (NHL). Blood. 140(Supplement 1). 12059–12060. 3 indexed citations
8.
Novick, Steven, et al.. (2022). A comparison of statistical methods for animal oncology studies. Pharmaceutical Statistics. 22(1). 112–127. 3 indexed citations
9.
Novick, Steven, et al.. (2020). A Bayesian Statistical Approach to Continuous Qualification of a Bioassay. PDA Journal of Pharmaceutical Science and Technology. 75(1). 8–23. 1 indexed citations
10.
OGASAWARA, K., Kathryn J. Newhall, Stephen E. Maxwell, et al.. (2019). Population Pharmacokinetics of an Anti-PD-L1 Antibody, Durvalumab in Patients with Hematologic Malignancies. Clinical Pharmacokinetics. 59(2). 217–227. 24 indexed citations
11.
Yang, Harry & Steven Novick. (2019). Bayesian Analysis with R for Drug Development: Concepts, Algorithms, and Case Studies. 3 indexed citations
12.
Novick, Steven, et al.. (2016). Setting Alert and Action Limits in the Presence of Significant Amount of Censoring in Data. PDA Journal of Pharmaceutical Science and Technology. 71(1). 20–32. 6 indexed citations
13.
Zhang, Hefei, Binfeng Xia, Jennifer Sheng, et al.. (2014). Application of Physiologically Based Absorption Modeling to Formulation Development of a Low Solubility, Low Permeability Weak Base: Mechanistic Investigation of Food Effect. AAPS PharmSciTech. 15(2). 400–406. 29 indexed citations
14.
Wang, Ruolan, Steven Novick, James B. Mangum, et al.. (2014). The Acute Extracellular Flux (XF) Assay to Assess Compound Effects on Mitochondrial Function. SLAS DISCOVERY. 20(3). 422–429. 24 indexed citations
15.
Novick, Steven, et al.. (2014). Dissolution Curve Comparisons Through theF2Parameter, a Bayesian Extension of thef2Statistic. Journal of Biopharmaceutical Statistics. 25(2). 351–371. 10 indexed citations
16.
Yang, Harry, Steven Novick, & David LeBlond. (2014). Testing Assay Linearity Over a Pre-Specified Range. Journal of Biopharmaceutical Statistics. 25(2). 339–350. 3 indexed citations
17.
Novick, Steven, et al.. (2013). The Effect of Initial Purity on the Stability of Solutions in Storage. SLAS DISCOVERY. 19(2). 308–316. 5 indexed citations
18.
Novick, Steven, et al.. (2012). Development of a high-throughput electrophysiological assay for the human ether-à-go-go related potassium channel hERG. Journal of Pharmacological and Toxicological Methods. 67(1). 33–44. 41 indexed citations
19.
Novick, Steven, Karen Chiswell, & John J. Peterson. (2011). A Bayesian Approach to Show Assay Equivalence with Replicate Measurements Over a Specified Response Range. Statistics in Biopharmaceutical Research. 4(2). 102–117. 3 indexed citations
20.

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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