Author

Ali Ebrahim

University of California San DiegoORCID 0000-0002-4009-2128Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Ali Ebrahim1 paper

Biology Disciplines

Click to filter author papers

Systems Biology· 3

Signature Assays, Organisms & Methods

Click to filter · or open tag

Approach:statistical model· 3 Research Focus:benchmarking· 2 Organism:E. coli· 2 Assay:metabolomics· 2 Assay:proteomics· 2 Research Focus:software / tool· 2 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1

Frequent Co-Authors

Bernhard Ørn PalssoniD· 3 shared Colton J. LloydiD· 3 shared Laurence YangiD· 3 shared Edward CatoiuiD· 1 shared Edward J. O’Brien· 1 shared Joanne K. LiuiD· 1 shared Jonathan M. MonkiD· 1 shared Michael A. SaundersiD· 1 shared

Activity by Year

2018-2021 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 27 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

3 shared papersSystems Biology

Bernhard Ørn PalssonORCID

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Computation of condition-dependent proteome allocation reveals variability in the macro and micro nutrient requirements for growth

Colton J. Lloyd, Jonathan M. Monk, Laurence Yang, Ali Ebrahim, Bernhard Ørn Palsson

The paper uses genome-scale models to compute proteome allocation under different conditions, revealing variability in cofactor use and protein composition for E. coli growth.

PLoS Computational Biology · Jun 23, 2021Peer-reviewedSystems Biology

DynamicME: Dynamic simulation and refinement of integrated models of metabolism and protein expression

Laurence Yang, Ali Ebrahim, Colton J. Lloyd, Michael A. Saunders, Bernhard Ørn Palsson

DynamicME simulates and refines integrated metabolism and protein expression models using time-course data, accurately predicting substrate utilization and expression profiles.

BMC Systems Biology · Jan 9, 2019Peer-reviewedSystems Biology

COBRAme: A Computational Framework for Models of Metabolism and Gene Expression

Colton J. Lloyd, Ali Ebrahim, Laurence Yang, Zachary A. King, Edward Catoiu, Edward J. O’Brien, Joanne K. Liu, Bernhard Ørn Palsson

COBRAme is a software framework for building and simulating ME-models, enabling efficient reconstruction and analysis of genome-scale models of metabolism and gene expression.

PLoS Computational Biology · Jul 5, 2018Peer-reviewedSystems Biology