Martin A. Newman

3.6k total citations · 2 hit papers
16 papers, 2.9k citations indexed

About

Martin A. Newman is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Martin A. Newman has authored 16 papers receiving a total of 2.9k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 7 papers in Cancer Research and 2 papers in Genetics. Recurrent topics in Martin A. Newman's work include MicroRNA in disease regulation (7 papers), RNA Research and Splicing (5 papers) and CRISPR and Genetic Engineering (4 papers). Martin A. Newman is often cited by papers focused on MicroRNA in disease regulation (7 papers), RNA Research and Splicing (5 papers) and CRISPR and Genetic Engineering (4 papers). Martin A. Newman collaborates with scholars based in United States, Netherlands and Germany. Martin A. Newman's co-authors include Scott M. Hammond, J. Michael Thomson, Joel S. Parker, Elizabeth Morin‐Kensicki, Tricia M. Wright, Diana O. Perkins, Clark Jeffries, Jianping Jin, L. Fredrik Jarskog and Heeyoung Seok and has published in prestigious journals such as Nature, Nucleic Acids Research and Genes & Development.

In The Last Decade

Martin A. Newman

14 papers receiving 2.9k citations

Hit Papers

2 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.

Extensive post-transcriptional regulation of microRNAs and its implications for cancer

2006 691 citations J. Michael Thomson, Martin A. Newman et al. Genes & Development profile →
Lin-28 interaction with the Let-7 precursor loop mediates regulated microRNA processing

2008 577 citations Martin A. Newman, J. Michael Thomson et al. RNA profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Martin A. Newman United States	12	2.6k	2.0k	182	116	105	16	2.9k
Katlin B. Massirer Brazil	16	1.7k 0.7×	1.1k 0.5×	84 0.5×	108 0.9×	170 1.6×	44	2.1k
Jun Cho South Korea	11	1.8k 0.7×	1.0k 0.5×	97 0.5×	69 0.6×	79 0.8×	20	2.2k
Trinna Cuellar United States	16	1.6k 0.6×	974 0.5×	160 0.9×	57 0.5×	28 0.3×	20	1.9k
Aibin He China	32	2.9k 1.1×	936 0.5×	366 2.0×	128 1.1×	58 0.6×	61	3.4k
Gen Shinoda United States	11	1.2k 0.5×	704 0.4×	117 0.6×	34 0.3×	75 0.7×	14	1.7k
Sergey Paushkin United States	24	4.3k 1.7×	580 0.3×	205 1.1×	153 1.3×	39 0.4×	31	4.7k
Carla P. Concepcion United States	8	1.1k 0.4×	722 0.4×	173 1.0×	46 0.4×	40 0.4×	8	1.4k
Alexander Y. Maslov United States	19	1.2k 0.5×	525 0.3×	264 1.5×	53 0.5×	146 1.4×	45	1.8k
Martin Teichmann France	29	2.6k 1.0×	350 0.2×	345 1.9×	176 1.5×	64 0.6×	47	3.0k
Yuning Wei China	10	1.3k 0.5×	882 0.4×	163 0.9×	52 0.4×	22 0.2×	15	1.7k

Countries citing papers authored by Martin A. Newman

Since Specialization

Citations

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

Fields of papers citing papers by Martin A. Newman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Martin A. Newman. 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 Martin A. Newman. The network helps show where Martin A. Newman may publish in the future.

Co-authorship network of co-authors of Martin A. Newman

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

All Works

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16 of 16 papers shown

Newman, Martin A., et al.. (2025). Non-cell-autonomous regulation of mTORC2 by Hedgehog signaling maintains lipid homeostasis. Cell Reports. 44(1). 115191–115191.

Breen, Peter C., et al.. (2024). The F-box protein FBXL-5 governs vitellogenesis and lipid homeostasis in C. elegans. Frontiers in Cell and Developmental Biology. 12. 1389077–1389077. 1 indexed citations

Cohen, Natalie R., et al.. (2024). A novel gain-of-function mutation in sgk-1 partially suppresses mTORC2 defects. PubMed. 2024.

Newman, Martin A., Fei Ji, Sylvia E. J. Fischer, et al.. (2018). The surveillance of pre-mRNA splicing is an early step in C. elegans RNAi of endogenous genes. Genes & Development. 32(9-10). 670–681. 24 indexed citations

Newman, Martin A. & Frederick M. Ausubel. (2016). Introduction to Gene Editing and Manipulation Using CRISPR/Cas9 Technology. Current Protocols in Molecular Biology. 115(1). 31.4.1–31.4.6. 6 indexed citations

Phillips, Carolyn M., Brooke E. E. Montgomery, Peter C. Breen, et al.. (2014). MUT-14 and SMUT-1 DEAD Box RNA Helicases Have Overlapping Roles in Germline RNAi and Endogenous siRNA Formation. Current Biology. 24(8). 839–844. 42 indexed citations

Tabach, Yuval, Allison C. Billi, Gabriel D. Hayes, et al.. (2012). Identification of small RNA pathway genes using patterns of phylogenetic conservation and divergence. Nature. 493(7434). 694–698. 111 indexed citations

Newman, Martin A., et al.. (2011). Deep sequencing of microRNA precursors reveals extensive 3′ end modification. RNA. 17(10). 1795–1803. 97 indexed citations

Xu, Jie, Wei Ma, Chong Qiao, et al.. (2011). Determinants of mRNA recognition and translation regulation by Lin28. Nucleic Acids Research. 40(8). 3574–3584. 31 indexed citations

10.

Newman, Martin A. & Scott M. Hammond. (2010). Emerging paradigms of regulated microRNA processing. Genes & Development. 24(11). 1086–1092. 211 indexed citations

11.

Dangi‐Garimella, Surabhi, Jieun Yun, Eva M. Eves, et al.. (2009). Raf kinase inhibitory protein suppresses a metastasis signalling cascade involving LIN28 and let‐7. The EMBO Journal. 28(4). 347–358. 293 indexed citations

12.

Newman, Martin A. & Scott M. Hammond. (2009). Lin-28: An early embryonic sentinel that blocks Let-7 biogenesis. The International Journal of Biochemistry & Cell Biology. 42(8). 1330–1333. 22 indexed citations

13.

Newman, Martin A., J. Michael Thomson, & Scott M. Hammond. (2008). Lin-28 interaction with the Let-7 precursor loop mediates regulated microRNA processing. RNA. 14(8). 1539–1549. 577 indexed citations breakdown →

14.

Perkins, Diana O., Clark Jeffries, L. Fredrik Jarskog, et al.. (2007). microRNA expression in the prefrontal cortex of individuals with schizophrenia and schizoaffective disorder. Genome biology. 8(2). R27–R27. 446 indexed citations

15.

Tatsuguchi, Mariko, Heeyoung Seok, Thomas E. Callis, et al.. (2007). Expression of microRNAs is dynamically regulated during cardiomyocyte hypertrophy. Journal of Molecular and Cellular Cardiology. 42(6). 1137–1141. 361 indexed citations

16.

Thomson, J. Michael, Martin A. Newman, Joel S. Parker, et al.. (2006). Extensive post-transcriptional regulation of microRNAs and its implications for cancer. Genes & Development. 20(16). 2202–2207. 691 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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