Faraz Faghri

12.1k total citations · 3 hit papers
27 papers, 1.8k citations indexed

About

Faraz Faghri is a scholar working on Molecular Biology, Neurology and Information Systems. According to data from OpenAlex, Faraz Faghri has authored 27 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Neurology and 3 papers in Information Systems. Recurrent topics in Faraz Faghri's work include Parkinson's Disease Mechanisms and Treatments (7 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). Faraz Faghri is often cited by papers focused on Parkinson's Disease Mechanisms and Treatments (7 papers), Bioinformatics and Genomic Networks (4 papers) and Gene expression and cancer classification (4 papers). Faraz Faghri collaborates with scholars based in United States, United Kingdom and Germany. Faraz Faghri's co-authors include Roy H. Campbell, Miles Efron, Saurabh Sinha, Michael C. Schatz, Gene E. Robinson, Ravishankar K. Iyer, Zachary Stephens, ChengXiang Zhai, Mike A. Nalls and Andrew Singleton and has published in prestigious journals such as Neuron, Nature Neuroscience and PLoS ONE.

In The Last Decade

Faraz Faghri

24 papers receiving 1.7k citations

Hit Papers

align trajectories sort by overperformance

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.

Big Data: Astronomical or Genomical?

2015 744 citations Faraz Faghri, Roy H. Campbell et al. profile →
Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis

2021 229 citations Ruilin Tian, Jason Hong et al. Nature Neuroscience profile →
Virus exposure and neurodegenerative disease risk across national biobanks

2023 175 citations Kristin Levine, Hampton L. Leonard et al. Neuron profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Faraz Faghri United States	15	810	284	202	192	182	27	1.8k
Duygu Ucar United States	25	1.9k 2.3×	134 0.5×	57 0.3×	103 0.5×	352 1.9×	55	3.1k
Carlo Vittorio Cannistraci Italy	31	937 1.2×	340 1.2×	84 0.4×	67 0.3×	88 0.5×	96	2.7k
Rosalba Giugno Italy	31	1.5k 1.9×	508 1.8×	99 0.5×	41 0.2×	111 0.6×	108	2.8k
Qing Zhu China	22	2.3k 2.8×	395 1.4×	60 0.3×	84 0.4×	286 1.6×	59	3.7k
Ding-fang Bu China	13	1.0k 1.3×	135 0.5×	58 0.3×	206 1.1×	202 1.1×	42	2.2k
Javier Garcı́a-Garcı́a Spain	18	1.7k 2.1×	83 0.3×	48 0.2×	66 0.3×	256 1.4×	46	2.6k
Andrea Visconti Italy	19	248 0.3×	149 0.5×	124 0.6×	82 0.4×	42 0.2×	62	1.3k
Mohamed Abouelhoda Saudi Arabia	20	822 1.0×	335 1.2×	40 0.2×	21 0.1×	388 2.1×	72	1.6k

Countries citing papers authored by Faraz Faghri

Since Specialization

Citations

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

Fields of papers citing papers by Faraz Faghri

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faraz Faghri

This figure shows the co-authorship network connecting the top 25 collaborators of Faraz Faghri. A scholar is included among the top collaborators of Faraz Faghri 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 Faraz Faghri. Faraz Faghri 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:

20 of 20 papers shown

Levine, Kristin, Jun Han, Hirotaka Iwaki, et al.. (2025). Sleep disturbances as risk factors for neurodegeneration later in life. ORCA Online Research @Cardiff. 1(1). 2 indexed citations

Herzog, Chiara, Jesse R. Poganik, Nir Barzilai, et al.. (2025). Biomarkers of Aging– NIA Joint Symposium 2024: New Insights Into Aging Biomarkers. Aging Cell. 24(7). e70124–e70124.

Alvarado, Chelsea X., Mary B. Makarious, Dan Vitale, et al.. (2025). omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases. The American Journal of Human Genetics. 112(9). 2248–2248.

Vitale, Dan, Mathew J. Koretsky, M R James, et al.. (2024). GenoTools: an open-source Python package for efficient genotype data quality control and analysis. G3 Genes Genomes Genetics. 15(1). 2 indexed citations

Makarious, Mary B., Dan Vitale, Andrew Singleton, et al.. (2024). Federated learning for multi-omics: A performance evaluation in Parkinson’s disease. Patterns. 5(3). 100945–100945. 11 indexed citations

Faghri, Faraz, et al.. (2024). Instruction Tuning Large Language Models to Understand Electronic Health Records. 54772–54786.

Alvarado, Chelsea X., Mary B. Makarious, Dan Vitale, et al.. (2024). omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases. The American Journal of Human Genetics. 111(1). 150–164. 4 indexed citations

Kaur, Rachneet, Mathew J. Koretsky, Hirotaka Iwaki, et al.. (2023). Application of Aligned-UMAP to longitudinal biomedical studies. Patterns. 4(6). 100741–100741. 11 indexed citations

Alvarado, Chelsea X., Mary B. Makarious, Dan Vitale, et al.. (2023). omicSynth: an open multi‐omic community resource for identifying druggable targets across neurodegenerative diseases. Alzheimer s & Dementia. 19(S24). 1 indexed citations

10.

Reilly, Luke, E. C. Lara, Daniel M. Ramos, et al.. (2023). A fully automated FAIMS-DIA mass spectrometry-based proteomic pipeline. Cell Reports Methods. 3(10). 100593–100593. 19 indexed citations

11.

Levine, Kristin, Hampton L. Leonard, Cornelis Blauwendraat, et al.. (2023). Virus exposure and neurodegenerative disease risk across national biobanks. Neuron. 111(7). 1086–1093.e2. 175 indexed citations breakdown →

12.

Dräger, Nina M., Sydney M. Sattler, Cindy Huang, et al.. (2022). A CRISPRi/a platform in human iPSC-derived microglia uncovers regulators of disease states. Nature Neuroscience. 25(9). 1149–1162. 123 indexed citations

13.

Kaur, Rachneet, Sayed Hadi Hashemi, Hampton L. Leonard, et al.. (2022). Identification and prediction of Parkinson’s disease subtypes and progression using machine learning in two cohorts. npj Parkinson s Disease. 8(1). 172–172. 50 indexed citations

14.

González-Vidal, Aurora, Jordí Ortiz, Zhongbo Chen, et al.. (2022). PhenoExam: gene set analyses through integration of different phenotype databases. BMC Bioinformatics. 23(1). 567–567. 1 indexed citations

15.

Tian, Ruilin, Jason Hong, Sayed Hadi Hashemi, et al.. (2021). Genome-wide CRISPRi/a screens in human neurons link lysosomal failure to ferroptosis. Nature Neuroscience. 24(7). 1020–1034. 229 indexed citations breakdown →

16.

Nalls, Mike A., Cornelis Blauwendraat, Lana Sargent, et al.. (2021). Evidence for GRN connecting multiple neurodegenerative diseases. Brain Communications. 3(2). fcab095–fcab095. 27 indexed citations

17.

Ubaida‐Mohien, Ceereena, Ruin Moaddel, Ann Zenobia Moore, et al.. (2021). Proteomics and Epidemiological Models of Human Aging. Frontiers in Physiology. 12. 674013–674013. 14 indexed citations

18.

Faghri, Faraz & Mike A. Nalls. (2021). Uncovering the complexities of biological structures with network-based learning: An application in SARS-CoV-2. Patterns. 2(5). 100259–100259. 1 indexed citations

19.

Leonard, Hampton L., Cornelis Blauwendraat, Lynne Krohn, et al.. (2019). Genetic variability and potential effects on clinical trial outcomes: perspectives in Parkinson’s disease. Journal of Medical Genetics. 57(5). 331–338. 40 indexed citations

20.

Zhou, Yuqian, et al.. (2019). Analysis and prediction of unplanned intensive care unit readmission using recurrent neural networks with long short-term memory. PLoS ONE. 14(7). e0218942–e0218942. 111 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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