Sandra E. Sinisi

969 total citations
10 papers, 669 citations indexed

About

Sandra E. Sinisi is a scholar working on Statistics and Probability, Virology and Artificial Intelligence. According to data from OpenAlex, Sandra E. Sinisi has authored 10 papers receiving a total of 669 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Statistics and Probability, 3 papers in Virology and 3 papers in Artificial Intelligence. Recurrent topics in Sandra E. Sinisi's work include Statistical Methods and Inference (5 papers), HIV Research and Treatment (3 papers) and Hepatitis C virus research (3 papers). Sandra E. Sinisi is often cited by papers focused on Statistical Methods and Inference (5 papers), HIV Research and Treatment (3 papers) and Hepatitis C virus research (3 papers). Sandra E. Sinisi collaborates with scholars based in United States. Sandra E. Sinisi's co-authors include Mark J. van der Laan, Maya L. Petersen, Soo‐Yon Rhee, Eric C. Polley, Octavia Plesh, Stuart A. Gansky, Patricia B. Crawford, W. Jeffrey Fessel, Annette M. Molinaro and Oliver Bembom and has published in prestigious journals such as Statistics in Medicine, Epidemiology and Journal of Multivariate Analysis.

In The Last Decade

Sandra E. Sinisi

10 papers receiving 638 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Sandra E. Sinisi United States	8	322	82	66	60	49	10	669
Michele Nichols United States	17	366 1.1×	39 0.5×	38 0.6×	54 0.9×	24 0.5×	23	1.6k
Lueping Zhao United States	10	320 1.0×	57 0.7×	63 1.0×	31 0.5×	12 0.2×	13	740
Sangita Kulathinal Finland	14	187 0.6×	58 0.7×	26 0.4×	23 0.4×	27 0.6×	59	864
Baoluo Sun United States	9	185 0.6×	40 0.5×	45 0.7×	23 0.4×	24 0.5×	19	561
Emily M. Mitchell United States	14	128 0.4×	46 0.6×	40 0.6×	65 1.1×	31 0.6×	33	887
Jing Huang United States	16	52 0.2×	75 0.9×	42 0.6×	22 0.4×	52 1.1×	87	818
Yongyi Min United States	6	382 1.2×	90 1.1×	104 1.6×	11 0.2×	17 0.3×	7	764
John D. Emerson United States	14	251 0.8×	106 1.3×	36 0.5×	8 0.1×	17 0.3×	48	1.0k
Mark J. van der Laan United States	5	583 1.8×	110 1.3×	82 1.2×	11 0.2×	37 0.8×	8	747
Matteo Quartagno United Kingdom	14	193 0.6×	73 0.9×	46 0.7×	15 0.3×	75 1.5×	39	715

Countries citing papers authored by Sandra E. Sinisi

Since Specialization

Citations

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

Fields of papers citing papers by Sandra E. Sinisi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sandra E. Sinisi. 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 Sandra E. Sinisi. The network helps show where Sandra E. Sinisi may publish in the future.

Co-authorship network of co-authors of Sandra E. Sinisi

This figure shows the co-authorship network connecting the top 25 collaborators of Sandra E. Sinisi. A scholar is included among the top collaborators of Sandra E. Sinisi 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 Sandra E. Sinisi. Sandra E. Sinisi 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

Bembom, Oliver, Maya L. Petersen, Soo‐Yon Rhee, et al.. (2008). Biomarker discovery using targeted maximum‐likelihood estimation: Application to the treatment of antiretroviral‐resistant HIV infection. Statistics in Medicine. 28(1). 152–172. 36 indexed citations

Sinisi, Sandra E., Eric C. Polley, Maya L. Petersen, Soo‐Yon Rhee, & Mark J. van der Laan. (2007). Super Learning: An Application to the Prediction of HIV-1 Drug Resistance. Statistical Applications in Genetics and Molecular Biology. 6(1). Article7–Article7. 167 indexed citations

Petersen, Maya, Annette M. Molinaro, Sandra E. Sinisi, & Mark J. van der Laan. (2007). Cross-validated bagged learning. Journal of Multivariate Analysis. 98(9). 1693–1704. 10 indexed citations

Petersen, Maya L., Sandra E. Sinisi, & Mark J. van der Laan. (2006). Estimation of Direct Causal Effects. Epidemiology. 17(3). 276–284. 261 indexed citations

Sinisi, Sandra E., Maya L. Petersen, & Mark J. van der Laan. (2006). Super Learning: An Application to Prediction of HIV-1 Drug Susceptibility. Collection of Biostatistics Research Archive. 2 indexed citations

Sinisi, Sandra E., Romain Neugebauer, & Mark J. van der Laan. (2006). Cross-Validated Bagged Prediction of Survival. Statistical Applications in Genetics and Molecular Biology. 5(1). 4 indexed citations

Sinisi, Sandra E., et al.. (2005). Multiple Testing and Data Adaptive Regression: An Application to HIV-1 Sequence Data.. Statistical Applications in Genetics and Molecular Biology. 4(1). Article8–Article8. 10 indexed citations

Plesh, Octavia, Sandra E. Sinisi, Patricia B. Crawford, & Stuart A. Gansky. (2005). Diagnoses based on the Research Diagnostic Criteria for Temporomandibular Disorders in a biracial population of young women.. PubMed. 19(1). 65–75. 48 indexed citations

Sinisi, Sandra E. & Mark J. van der Laan. (2004). Deletion/Substitution/Addition Algorithm in Learning with Applications in Genomics. Statistical Applications in Genetics and Molecular Biology. 3(1). 1–38. 116 indexed citations

10.

Dudoit, Sandrine, et al.. (2003). Loss-based estimation with cross-validation. ACM SIGKDD Explorations Newsletter. 5(2). 56–68. 15 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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