Edward Tom

797 total citations · 1 hit paper
5 papers, 657 citations indexed

About

Edward Tom is a scholar working on Molecular Biology, Oncology and Endocrinology, Diabetes and Metabolism. According to data from OpenAlex, Edward Tom has authored 5 papers receiving a total of 657 indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Molecular Biology, 2 papers in Oncology and 2 papers in Endocrinology, Diabetes and Metabolism. Recurrent topics in Edward Tom's work include Cancer-related Molecular Pathways (2 papers), Thyroid Cancer Diagnosis and Treatment (2 papers) and Molecular Biology Techniques and Applications (2 papers). Edward Tom is often cited by papers focused on Cancer-related Molecular Pathways (2 papers), Thyroid Cancer Diagnosis and Treatment (2 papers) and Molecular Biology Techniques and Applications (2 papers). Edward Tom collaborates with scholars based in United States, Mexico and Italy. Edward Tom's co-authors include Renbin Zhao, David H. Mack, Kurt Gish, Maureen E. Murphy, Arnold J. Levine, William H. Hoffman, Yuxin Yin, Daniel A. Notterman, P. Sean Walsh and Giulia C. Kennedy and has published in prestigious journals such as Genes & Development, The Journal of Clinical Endocrinology & Metabolism and BMC Pulmonary Medicine.

In The Last Decade

Edward Tom

5 papers receiving 638 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Analysis of p53-regulated gene expression patterns using oligonucleotide arrays

2000 538 citations Renbin Zhao, Kurt Gish et al. Genes & Development profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Edward Tom United States	5	469	365	97	90	77	5	657
Leland W. K. Chung United States	8	454 1.0×	185 0.5×	266 2.7×	49 0.5×	28 0.4×	9	732
Verónica Calvo United States	9	265 0.6×	218 0.6×	167 1.7×	26 0.3×	33 0.4×	13	513
Woo-Jeong Jeong South Korea	12	497 1.1×	260 0.7×	94 1.0×	14 0.2×	23 0.3×	14	665
Natacha Bohin United States	9	318 0.7×	162 0.4×	101 1.0×	34 0.4×	11 0.1×	10	542
LaTonia Taliaferro‐Smith United States	8	362 0.8×	240 0.7×	159 1.6×	35 0.4×	12 0.2×	13	556
Paula Gutierrez‐Martinez Spain	10	763 1.6×	360 1.0×	138 1.4×	276 3.1×	12 0.2×	12	1.0k
Sandy D. Markowitz United States	2	528 1.1×	221 0.6×	404 4.2×	23 0.3×	19 0.2×	2	735
Chaitanyananda B. Koppikar India	3	390 0.8×	421 1.2×	174 1.8×	12 0.1×	42 0.5×	3	645
Julia Bárdos United Kingdom	10	536 1.1×	179 0.5×	366 3.8×	14 0.2×	26 0.3×	13	777
Angel Ciprés Spain	9	350 0.7×	159 0.4×	142 1.5×	20 0.2×	23 0.3×	10	607

Countries citing papers authored by Edward Tom

Since Specialization

Citations

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

Fields of papers citing papers by Edward Tom

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward Tom

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

All Works

Sort: Min cites: Since: Top N: Style:

5 of 5 papers shown

1.

Choi, Yoonha, Jiayi Lu, Zhanzhi Hu, et al.. (2017). Analytical performance of Envisia: a genomic classifier for usual interstitial pneumonia. BMC Pulmonary Medicine. 17(1). 141–141. 19 indexed citations

2.

Kloos, Richard T., Jessica Reynolds, P. Sean Walsh, et al.. (2013). Does Addition ofBRAFV600E Mutation Testing Modify Sensitivity or Specificity of the Afirma Gene Expression Classifier in Cytologically Indeterminate Thyroid Nodules?. The Journal of Clinical Endocrinology & Metabolism. 98(4). E761–E768. 51 indexed citations

3.

Walsh, P. Sean, Jonathan I. Wilde, Edward Tom, et al.. (2012). Analytical Performance Verification of a Molecular Diagnostic for Cytology-Indeterminate Thyroid Nodules. The Journal of Clinical Endocrinology & Metabolism. 97(12). E2297–E2306. 45 indexed citations

4.

Hevezi, Peter, Edward Tom, Keith E. Wilson, et al.. (2011). Gene expression patterns in livers of Hispanic patients infected with hepatitis C virus. Autoimmunity. 44(7). 532–542. 4 indexed citations

5.

Zhao, Renbin, Kurt Gish, Maureen E. Murphy, et al.. (2000). Analysis of p53-regulated gene expression patterns using oligonucleotide arrays. Genes & Development. 14(8). 981–993. 538 indexed citations breakdown →

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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