Ali Ebrahim

5.1k total citations · 2 hit papers
28 papers, 3.0k citations indexed

About

Ali Ebrahim is a scholar working on Molecular Biology, Biomedical Engineering and Genetics. According to data from OpenAlex, Ali Ebrahim has authored 28 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 6 papers in Biomedical Engineering and 5 papers in Genetics. Recurrent topics in Ali Ebrahim's work include Microbial Metabolic Engineering and Bioproduction (18 papers), Gene Regulatory Network Analysis (9 papers) and Bioinformatics and Genomic Networks (8 papers). Ali Ebrahim is often cited by papers focused on Microbial Metabolic Engineering and Bioproduction (18 papers), Gene Regulatory Network Analysis (9 papers) and Bioinformatics and Genomic Networks (8 papers). Ali Ebrahim collaborates with scholars based in United States, Denmark and Germany. Ali Ebrahim's co-authors include Bernhard Ø. Palsson, Joshua A. Lerman, Daniel R. Hyduke, Zachary A. King, Nathan E. Lewis, Andreas Dräger, Stephen Federowicz, Adam M. Feist, Philip Miller and Edward J. O’Brien and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.

In The Last Decade

Ali Ebrahim

28 papers receiving 3.0k 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.

COBRApy: COnstraints-Based Reconstruction and Analysis for Python

2013 841 citations Ali Ebrahim, Joshua A. Lerman et al. BMC Systems Biology profile →
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models

2015 586 citations Zachary A. King, Andreas Dräger et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ali Ebrahim United States	19	2.6k	956	387	165	133	28	3.0k
Joshua A. Lerman United States	14	3.8k 1.4×	1.3k 1.4×	491 1.3×	161 1.0×	49 0.4×	15	4.1k
Christophe H. Schilling United States	21	4.8k 1.8×	1.7k 1.8×	378 1.0×	193 1.2×	142 1.1×	23	5.1k
Jeffrey D. Orth United States	9	5.2k 2.0×	2.0k 2.1×	520 1.3×	308 1.9×	110 0.8×	10	5.6k
Jan Schellenberger United States	13	2.7k 1.0×	986 1.0×	208 0.5×	137 0.8×	46 0.3×	16	2.9k
Nathan J. Hillson United States	30	2.5k 0.9×	807 0.8×	434 1.1×	105 0.6×	99 0.7×	78	3.3k
Isabel Rocha Portugal	32	2.6k 1.0×	1.2k 1.3×	224 0.6×	84 0.5×	39 0.3×	147	3.3k
Katy C. Kao United States	24	1.6k 0.6×	662 0.7×	537 1.4×	109 0.7×	33 0.2×	45	2.2k
Elliot Altman United States	30	2.9k 1.1×	1.1k 1.1×	777 2.0×	58 0.4×	86 0.6×	66	3.3k
Tom M Conrad United States	9	2.2k 0.9×	692 0.7×	613 1.6×	78 0.5×	29 0.2×	11	2.5k
Stephan Noack Germany	30	2.4k 0.9×	1.2k 1.2×	282 0.7×	74 0.4×	38 0.3×	115	3.0k

Countries citing papers authored by Ali Ebrahim

Since Specialization

Citations

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

Fields of papers citing papers by Ali Ebrahim

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Ebrahim

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

Schor, Jonathan S., Isabel Fulcher, Kartik K. Venkatesh, et al.. (2024). Using machine learning to predict the risk of developing hypertensive disorders of pregnancy using a contemporary nulliparous cohort. AJOG Global Reports. 4(4). 100386–100386. 2 indexed citations

Park, Joon Young, Sang‐Mok Lee, Ali Ebrahim, et al.. (2023). Model-driven experimental design workflow expands understanding of regulatory role of Nac in Escherichia coli. NAR Genomics and Bioinformatics. 5(1). lqad006–lqad006. 4 indexed citations

Fulcher, Isabel, et al.. (2023). Using machine learning to predict the risk of developing gestational diabetes using a contemporary cohort. American Journal of Obstetrics and Gynecology. 228(1). S752–S753. 1 indexed citations

Wen, Timothy, et al.. (2022). Random Forests for Accurate Prediction of the Risk of Hypertensive Disorders of Pregnancy at Term [A208]. Obstetrics and Gynecology. 139(1). 60S–61S. 2 indexed citations

Lloyd, Colton J., Jonathan M. Monk, Laurence Yang, Ali Ebrahim, & Bernhard Ø. Palsson. (2021). Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth. PLoS Computational Biology. 17(6). e1007817–e1007817. 7 indexed citations

Liu, Joanne K., Colton J. Lloyd, Mahmoud M. Al‐Bassam, et al.. (2019). Predicting proteome allocation, overflow metabolism, and metal requirements in a model acetogen. PLoS Computational Biology. 15(3). e1006848–e1006848. 49 indexed citations

Yang, Laurence, Ali Ebrahim, Colton J. Lloyd, Michael A. Saunders, & Bernhard Ø. Palsson. (2019). DynamicME: dynamic simulation and refinement of integrated models of metabolism and protein expression. BMC Systems Biology. 13(1). 2–2. 44 indexed citations

Lloyd, Colton J., Ali Ebrahim, Laurence Yang, et al.. (2018). COBRAme: A computational framework for genome-scale models of metabolism and gene expression. PLoS Computational Biology. 14(7). e1006302–e1006302. 107 indexed citations

Latif, Haythem, Stephen Federowicz, Ali Ebrahim, et al.. (2018). ChIP-exo interrogation of Crp, DNA, and RNAP holoenzyme interactions. PLoS ONE. 13(5). e0197272–e0197272. 14 indexed citations

10.

Ebrahim, Ali, et al.. (2017). Factors Influencing Job Satisfaction and Turnover Intention among Coronary Care Unit Nurses in Bahrain. 4(1). 7 indexed citations

11.

Yang, Laurence, Ding Ma, Ali Ebrahim, et al.. (2016). solveME: fast and reliable solution of nonlinear ME models. BMC Bioinformatics. 17(1). 391–391. 35 indexed citations

12.

Yang, Laurence, et al.. (2016). Principles of proteome allocation are revealed using proteomic data and genome-scale models. Scientific Reports. 6(1). 36734–36734. 26 indexed citations

13.

Ebrahim, Ali, Elizabeth Brunk, Justin Tan, et al.. (2016). Multi-omic data integration enables discovery of hidden biological regularities. Nature Communications. 7(1). 13091–13091. 119 indexed citations

14.

King, Zachary A., Andreas Dräger, Ali Ebrahim, et al.. (2015). Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways. PLoS Computational Biology. 11(8). e1004321–e1004321. 247 indexed citations

15.

King, Zachary A., Andreas Dräger, Philip Miller, et al.. (2015). BiGG Models: A platform for integrating, standardizing and sharing genome-scale models. Nucleic Acids Research. 44(D1). D515–D522. 586 indexed citations breakdown →

16.

Sandberg, Troy E., Margit Pedersen, Ryan A. LaCroix, et al.. (2014). Evolution of Escherichia coli to 42 °C and Subsequent Genetic Engineering Reveals Adaptive Mechanisms and Novel Mutations. Molecular Biology and Evolution. 31(10). 2647–2662. 127 indexed citations

17.

Bordbar, Aarash, Harish Nagarajan, Nathan E. Lewis, et al.. (2014). Minimal metabolic pathway structure is consistent with associated biomolecular interactions. Molecular Systems Biology. 10(7). 737–737. 33 indexed citations

18.

Federowicz, Stephen, Donghyuk Kim, Ali Ebrahim, et al.. (2014). Determining the Control Circuitry of Redox Metabolism at the Genome-Scale. PLoS Genetics. 10(4). e1004264–e1004264. 53 indexed citations

19.

Ebrahim, Ali, Joshua A. Lerman, Bernhard Ø. Palsson, & Daniel R. Hyduke. (2013). COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Systems Biology. 7(1). 74–74. 841 indexed citations breakdown →

20.

Nagarajan, Harish, Merve Şahin, Juan Nogales, et al.. (2013). Characterizing acetogenic metabolism using a genome-scale metabolic reconstruction of Clostridium ljungdahlii. Microbial Cell Factories. 12(1). 118–118. 134 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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