Fadi Towfic

2.7k total citations
46 papers, 1.2k citations indexed

About

Fadi Towfic is a scholar working on Molecular Biology, Hematology and Oncology. According to data from OpenAlex, Fadi Towfic has authored 46 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 19 papers in Hematology and 10 papers in Oncology. Recurrent topics in Fadi Towfic's work include Multiple Myeloma Research and Treatments (19 papers), Protein Degradation and Inhibitors (14 papers) and Peptidase Inhibition and Analysis (6 papers). Fadi Towfic is often cited by papers focused on Multiple Myeloma Research and Treatments (19 papers), Protein Degradation and Inhibitors (14 papers) and Peptidase Inhibition and Analysis (6 papers). Fadi Towfic collaborates with scholars based in United States, United Kingdom and Canada. Fadi Towfic's co-authors include Anjan Thakurta, Erin Flynt, Maxim N. Artyomov, María Ortiz, Vasant Honavar, Ramnik J. Xavier, Emil R. Unanue, Boris Calderón, Javier A. Carrero and Drena Dobbs and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Chemical Physics and Blood.

In The Last Decade

Fadi Towfic

45 papers receiving 1.2k citations

Peers

Fadi Towfic

HEMAT

ONCOL

IMMUN

GENET

Sinisa Dovat United States

Prince George United States

Frédèrique Verdier France

Chris Bartholomew United Kingdom

Klara R. Klein United States

Julia M. Burkhart Germany

Wei Du United States

Yaomin Xu United States

Katherine Oravecz-Wilson United States

Joseph C. Marini United States

Sinisa Dovat United States

Fadi Towfic

1.0k ×1.3

705 ×2.0

HEMAT

280 ×1.1

ONCOL

366 ×1.6

IMMUN

128 ×0.7

GENET

Citations per year, relative to Fadi Towfic Fadi Towfic (= 1×) peers Sinisa Dovat

Countries citing papers authored by Fadi Towfic

Since Specialization

Citations

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

Fields of papers citing papers by Fadi Towfic

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fadi Towfic

This figure shows the co-authorship network connecting the top 25 collaborators of Fadi Towfic. A scholar is included among the top collaborators of Fadi Towfic 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 Fadi Towfic. Fadi Towfic 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

Hagner, Patrick R., Hsiling Chiu, Martino Colombo, et al.. (2022). Interactome of Aiolos/Ikaros Reveals Combination Rationale of Cereblon Modulators with HDAC Inhibitors in DLBCL. Clinical Cancer Research. 28(15). 3367–3377. 3 indexed citations

Ansari‐Pour, Naser, Mehmet Samur, Erin Flynt, et al.. (2022). Whole-genome analysis identifies novel drivers and high-risk double-hit events in relapsed/refractory myeloma. Blood. 141(6). 620–633. 22 indexed citations

Stong, Nicholas, Fadi Towfic, Mehmet Samur, et al.. (2022). The location of the t(4;14) translocation breakpoint within the NSD2 gene identifies a subset of patients with high-risk NDMM. Blood. 141(13). 1574–1583. 21 indexed citations

Gooding, Sarah, Naser Ansari‐Pour, Kübra Karagoz, et al.. (2022). Loss of COP9 signalosome genes at 2q37 is associated with IMiD resistance in multiple myeloma. Blood. 140(16). 1816–1821. 13 indexed citations

Towfic, Fadi, Erin Flynt, Nicholas Stong, et al.. (2021). Integrative multi-omics identifies high risk multiple myeloma subgroup associated with significant DNA loss and dysregulated DNA repair and cell cycle pathways. BMC Medical Genomics. 14(1). 295–295. 8 indexed citations

Gooding, Sarah, Naser Ansari‐Pour, Kübra Karagoz, et al.. (2021). Loss of COP9 Signalosome Gene-Containing 2q Region Is Associated with Lenalidomide and Pomalidomide Resistance in Myeloma Patients. Blood. 138(Supplement 1). 458–458.

Risueño, Alberto, Patrick R. Hagner, Fadi Towfic, et al.. (2020). Leveraging Gene Expression Subgroups to Classify DLBCL Patients and Enrich for Clinical Benefit to a Novel Agent. Blood. 135(13). 1008–1018. 11 indexed citations

Flynt, Erin, et al.. (2020). Prognosis, Biology, and Targeting of TP53 Dysregulation in Multiple Myeloma. Cells. 9(2). 287–287. 42 indexed citations

Bjorklund, Chad C., Jian Kang, Michael Amatangelo, et al.. (2019). Iberdomide (CC-220) is a potent cereblon E3 ligase modulator with antitumor and immunostimulatory activities in lenalidomide- and pomalidomide-resistant multiple myeloma cells with dysregulated CRBN. Leukemia. 34(4). 1197–1201. 144 indexed citations

10.

Ross, Colin J.D., Fadi Towfic, Jyoti Shankar, et al.. (2017). A pharmacogenetic signature of high response to Copaxone in late-phase clinical-trial cohorts of multiple sclerosis. Genome Medicine. 9(1). 50–50. 19 indexed citations

11.

Kolitz, Sarah, Fadi Towfic, Daphna Laifenfeld, et al.. (2015). Functional effects of the antigen glatiramer acetate are complex and tightly associated with its composition. Journal of Neuroimmunology. 290. 84–95. 17 indexed citations

12.

Kolitz, Sarah, Fadi Towfic, Jason Funt, et al.. (2015). Gene expression studies of a human monocyte cell line identify dissimilarities between differently manufactured glatiramoids. Scientific Reports. 5(1). 10191–10191. 15 indexed citations

13.

Fowler, Kevin, Jason Funt, Maxim N. Artyomov, et al.. (2015). Leveraging existing data sets to generate new insights into Alzheimer’s disease biology in specific patient subsets. Scientific Reports. 5(1). 14324–14324. 14 indexed citations

14.

Carrero, Javier A., Boris Calderón, Fadi Towfic, Maxim N. Artyomov, & Emil R. Unanue. (2014). Correction: Defining the Transcriptional and Cellular Landscape of Type 1 Diabetes in the NOD Mouse. PLoS ONE. 9(1). 2 indexed citations

15.

Towfic, Fadi, Jason Funt, Kevin Fowler, et al.. (2014). Comparing the Biological Impact of Glatiramer Acetate with the Biological Impact of a Generic. PLoS ONE. 9(1). e83757–e83757. 31 indexed citations

16.

Carrero, Javier A., Boris Calderón, Fadi Towfic, Maxim N. Artyomov, & Emil R. Unanue. (2013). Defining the Transcriptional and Cellular Landscape of Type 1 Diabetes in the NOD Mouse. PLoS ONE. 8(3). e59701–e59701. 93 indexed citations

17.

VanDussen, Kelli L., Ta‐Chiang Liu, Dalin Li, et al.. (2013). Genetic Variants Synthesize to Produce Paneth Cell Phenotypes That Define Subtypes of Crohn's Disease. Gastroenterology. 146(1). 200–209. 134 indexed citations

18.

Walia, Rasna R., Cornelia Caragea, Fadi Towfic, et al.. (2012). Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art. BMC Bioinformatics. 13(1). 89–89. 74 indexed citations

19.

Towfic, Fadi, et al.. (2010). Detection of gene orthology from gene co-expression and protein interaction networks. BMC Bioinformatics. 11(S3). S7–S7. 15 indexed citations

20.

Towfic, Fadi, et al.. (2009). Genetic Mutations Affecting the Success and Failure of HIV Regimens. Journal of Proteomics & Bioinformatics. 2(9). 372–379. 2 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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