Noa Rappaport

10.5k total citations · 3 hit papers
34 papers, 5.8k citations indexed

About

Noa Rappaport is a scholar working on Molecular Biology, Physiology and Genetics. According to data from OpenAlex, Noa Rappaport has authored 34 papers receiving a total of 5.8k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 8 papers in Physiology and 6 papers in Genetics. Recurrent topics in Noa Rappaport's work include Bioinformatics and Genomic Networks (10 papers), Metabolomics and Mass Spectrometry Studies (7 papers) and Gut microbiota and health (6 papers). Noa Rappaport is often cited by papers focused on Bioinformatics and Genomic Networks (10 papers), Metabolomics and Mass Spectrometry Studies (7 papers) and Gut microbiota and health (6 papers). Noa Rappaport collaborates with scholars based in United States, Israel and Austria. Noa Rappaport's co-authors include Doron Lancet, Marilyn Safran, Tsippi Iny Stein, Michal Twik, Inbar Plaschkes, Ron Nudel, Asher Kohn, Simon Fishilevich, Naomi Rosen and Gil Stelzer and has published in prestigious journals such as Nucleic Acids Research, Nature Medicine and Nature Communications.

In The Last Decade

Noa Rappaport

31 papers receiving 5.7k 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.

The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses

2016 3.2k citations Gil Stelzer, Naomi Rosen et al. Current Protocols in Bioinformatics profile →
GeneHancer: genome-wide integration of enhancers and target genes in GeneCards

2017 746 citations Simon Fishilevich, Ron Nudel et al. profile →
MalaCards: an amalgamated human disease compendium with diverse clinical and genetic annotation and structured search

2016 432 citations Noa Rappaport, Michal Twik et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Noa Rappaport United States	20	3.4k	809	743	572	500	34	5.8k
Inbar Plaschkes Israel	17	3.1k 0.9×	705 0.9×	670 0.9×	550 1.0×	305 0.6×	30	5.2k
Michal Twik Israel	8	2.8k 0.8×	706 0.9×	682 0.9×	561 1.0×	274 0.5×	8	4.8k
Ron Nudel Denmark	16	2.7k 0.8×	912 1.1×	647 0.9×	549 1.0×	276 0.6×	37	5.1k
Tsippi Iny Stein Israel	13	4.1k 1.2×	938 1.2×	1.0k 1.4×	811 1.4×	375 0.8×	13	6.9k
Gil Stelzer Israel	15	2.6k 0.8×	575 0.7×	620 0.8×	517 0.9×	262 0.5×	23	4.5k
Simon Fishilevich Israel	10	2.5k 0.7×	625 0.8×	622 0.8×	537 0.9×	242 0.5×	12	4.5k
Naomi Rosen Israel	8	3.5k 1.0×	776 1.0×	870 1.2×	711 1.2×	307 0.6×	13	5.9k
Asher Kohn Israel	4	2.5k 0.7×	614 0.8×	612 0.8×	518 0.9×	241 0.5×	5	4.3k
Dvir Dahary Israel	15	2.9k 0.9×	657 0.8×	744 1.0×	473 0.8×	226 0.5×	21	4.7k
Marc Legeay France	3	3.3k 1.0×	461 0.6×	876 1.2×	290 0.5×	300 0.6×	6	5.3k

Countries citing papers authored by Noa Rappaport

Since Specialization

Citations

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

Fields of papers citing papers by Noa Rappaport

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Noa Rappaport

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

All Works

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20 of 20 papers shown

Pflieger, Lance, et al.. (2025). Bile acids segregate metabolic syndrome in a cohort of 100 deeply phenotyped horses. Communications Biology. 8(1). 1711–1711.

Rappaport, Noa, et al.. (2025). Early Detection of Wellness-to-Disease Transitions in the AI Era: Implications for Pharmacology and Toxicology. The Annual Review of Pharmacology and Toxicology. 66(1). 41–64.

Wilmanski, Tomasz, Lisa Levy, Johanna W. Lampe, et al.. (2024). Microbial community-scale metabolic modelling predicts personalized short-chain fatty acid production profiles in the human gut. Nature Microbiology. 9(7). 1700–1712. 41 indexed citations

Diener, Christian, Tomasz Wilmanski, David L. Suskind, et al.. (2024). Aberrant bowel movement frequencies coincide with increased microbe-derived blood metabolites associated with reduced organ function. Cell Reports Medicine. 5(7). 101646–101646. 6 indexed citations

Yurkovich, James T., Simon J. Evans, Noa Rappaport, et al.. (2023). The transition from genomics to phenomics in personalized population health. Nature Reviews Genetics. 25(4). 286–302. 27 indexed citations

Burns, Adam R., Jack Wiedrick, Michal Maes, et al.. (2023). Proteomic changes induced by longevity-promoting interventions in mice. GeroScience. 46(2). 1543–1560. 2 indexed citations

Watanabe, Kengo, Tomasz Wilmanski, Christian Diener, et al.. (2023). Multiomic signatures of body mass index identify heterogeneous health phenotypes and responses to a lifestyle intervention. Nature Medicine. 29(4). 996–1008. 71 indexed citations

Diener, Christian, Chengzhen L. Dai, Tomasz Wilmanski, et al.. (2022). Genome–microbiome interplay provides insight into the determinants of the human blood metabolome. Nature Metabolism. 4(11). 1560–1572. 59 indexed citations

Wilmanski, Tomasz, Sergey A. Kornilov, Christian Diener, et al.. (2022). Heterogeneity in statin responses explained by variation in the human gut microbiome. Med. 3(6). 388–405.e6. 43 indexed citations

10.

Roper, Ryan, Venkata R. Duvvuri, Jason D. Goldman, et al.. (2022). Risk factors for severe COVID-19 differ by age for hospitalized adults. Scientific Reports. 12(1). 6568–6568. 37 indexed citations

11.

Zimmer, Anat, Yael Korem, Noa Rappaport, et al.. (2021). The geometry of clinical labs and wellness states from deeply phenotyped humans. Nature Communications. 12(1). 3578–3578. 10 indexed citations

12.

Törmäkangas, Timo, Noa Rappaport, Tomasz Wilmanski, et al.. (2021). Towards early risk biomarkers: serum metabolic signature in childhood predicts cardio-metabolic risk in adulthood. EBioMedicine. 72. 103611–103611. 23 indexed citations

13.

Wilmanski, Tomasz, Noa Rappaport, Christian Diener, Sean M. Gibbons, & Nathan D. Price. (2021). From taxonomy to metabolic output: what factors define gut microbiome health?. Gut Microbes. 13(1). 1–20. 29 indexed citations

14.

McFarland, Karen N., Carolina Wiesner, Awilda M. Rosario, et al.. (2021). Microglia show differential transcriptomic response to Aβ peptide aggregates ex vivo and in vivo. Life Science Alliance. 4(7). e202101108–e202101108. 17 indexed citations

15.

Magis, Andrew T., Noa Rappaport, Matthew P. Conomos, et al.. (2020). Untargeted longitudinal analysis of a wellness cohort identifies markers of metastatic cancer years prior to diagnosis. Scientific Reports. 10(1). 16275–16275. 15 indexed citations

16.

Wilmanski, Tomasz, Noa Rappaport, John C. Earls, et al.. (2019). Blood metabolome predicts gut microbiome α-diversity in humans. Nature Biotechnology. 37(10). 1217–1228. 217 indexed citations

17.

Stelzer, Gil, Naomi Rosen, Inbar Plaschkes, et al.. (2016). The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses. Current Protocols in Bioinformatics. 54(1). 1.30.1–1.30.33. 3231 indexed citations breakdown →

18.

Rappaport, Noa & Naama Barkai. (2011). Disentangling signaling gradients generated by equivalent sources. Journal of Biological Physics. 38(2). 267–278. 17 indexed citations

19.

Rappaport, Noa, et al.. (2005). The ups and downs of biological timers. Theoretical Biology and Medical Modelling. 2(1). 22–22. 8 indexed citations

20.

Raczynski, James M., et al.. (1994). Diagnoses, symptoms, and attribution of symptoms among black and white inpatients admitted for coronary heart disease.. American Journal of Public Health. 84(6). 951–956. 80 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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