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D-Index & Metrics

Biology and Biochemistry

D-Index
65
Citations
23401
World Ranking
8970
National Ranking
3985

Overview

Nathan E. Lewis is affiliated with the University of California, San Diego in the United States. Their research primarily spans the field of Biochemistry, Genetics and Molecular Biology, with a strong focus on several interconnected subfields such as Molecular Biology, Genetics, Immunology, Cell Biology, and Radiology, Nuclear Medicine and Imaging.

The research topics covered by Nathan E. Lewis include Viral Infectious Diseases and Gene Expression in Insects, Microbial Metabolic Engineering and Bioproduction, Glycosylation and Glycoproteins Research, CRISPR and Genetic Engineering, Gene Regulatory Network Analysis, Single-cell and spatial transcriptomics, and Monoclonal and Polyclonal Antibodies Research.

Recent papers authored or co-authored by Nathan E. Lewis include the following:

  • Deciphering cell-cell interactions and communication from gene expression (2020, Nature Reviews Genetics)
  • MEMOTE for standardized genome-scale metabolic model testing (2020, Nature Biotechnology)
  • Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor (2020, Cell Host & Microbe)
  • Prenatal Origins of ASD: The When, What, and How of ASD Development (2020, Trends in Neurosciences)
  • What are housekeeping genes? (2022, PLoS Computational Biology)

Nathan E. Lewis has collaborated frequently with a number of co-authors, including Austin W.T. Chiang, Benjamin P. Kellman, Erick Armingol, Hooman Hefzi, and Hratch Baghdassarian.

Their work has been published in multiple venues, with the most frequent including bioRxiv (Cold Spring Harbor Laboratory), Metabolic Engineering, The FASEB Journal, Nature Communications, and the Journal of Allergy and Clinical Immunology.

Best Publications

  • Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0

    Jan Schellenberger;Richard Que;Ronan M T Fleming;Ines Thiele

  • Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

    Laurent Heirendt;Sylvain Arreckx;Thomas Pfau;Sebastián N. Mendoza

  • BiGG Models: A platform for integrating, standardizing and sharing genome-scale models.

    Zachary A. King;Justin Lu;Andreas Dräger;Andreas Dräger;Philip Miller

  • Constraining the metabolic genotype–phenotype relationship using a phylogeny of in silico methods

    Nathan E. Lewis;Harish Nagarajan;Bernhard O. Palsson

  • The genomic sequence of the Chinese hamster ovary (CHO)-K1 cell line

    Xun Xu;Harish Nagarajan;Nathan E Lewis;Shengkai Pan

  • Deciphering cell-cell interactions and communication from gene expression.

    Erick Armingol;Adam Officer;Olivier Harismendy;Nathan E Lewis

  • Omic data from evolved E. coli are consistent with computed optimal growth from genome‐scale models

    Nathan E Lewis;Kim K Hixson;Tom M Conrad;Joshua A Lerman

  • Design and analysis of synthetic carbon fixation pathways.

    Arren Bar-Even;Elad Noor;Nathan E. Lewis;Nathan E. Lewis;Ron Milo

  • MEMOTE for standardized genome-scale metabolic model testing

    Christian Lieven;Moritz Emanuel Beber;Brett G. Olivier;Frank T. Bergmann

  • Virus-Receptor Interactions of Glycosylated SARS-CoV-2 Spike and Human ACE2 Receptor.

    Peng Zhao;Jeremy L. Praissman;Oliver C. Grant;Yongfei Cai

  • Genomic landscapes of Chinese hamster ovary cell lines as revealed by the Cricetulus griseus draft genome

    Nathan E Lewis;Xin Liu;Yuxiang Li;Harish Nagarajan

  • An enhanced CRISPR repressor for targeted mammalian gene regulation

    Nan Cher Yeo;Alejandro Chavez;Alissa Lance-Byrne;Yingleong Chan;Yingleong Chan

  • Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways.

    Zachary A. King;Andreas Dräger;Ali Ebrahim;Nikolaus Sonnenschein

  • Combinatorial CRISPR–Cas9 screens for de novo mapping of genetic interactions

    John Paul Shen;Dongxin Zhao;Roman Sasik;Jens Luebeck

  • Recon 2.2: from reconstruction to model of human metabolism

    Neil Swainston;Kieran Smallbone;Hooman Hefzi;Paul D. Dobson

  • Microbial laboratory evolution in the era of genome‐scale science

    Tom M Conrad;Nathan E Lewis;Bernhard Ø Palsson

  • The role of replicates for error mitigation in next-generation sequencing.

    Kimberly Robasky;Nathan E. Lewis;George M. Church

  • In silico method for modelling metabolism and gene product expression at genome scale

    Joshua A. Lerman;Daniel R. Hyduke;Haythem Latif;Vasiliy A. Portnoy

  • Network context and selection in the evolution to enzyme specificity

    Hojung Nam;Nathan E. Lewis;Nathan E. Lewis;Joshua A. Lerman;Dae-Hee Lee

  • Large-scale in silico modeling of metabolic interactions between cell types in the human brain

    Nathan E. Lewis;Gunnar Schramm;Gunnar Schramm;Aarash Bordbar;Jan Schellenberger

Frequent Co-Authors

Bernhard O. Palsson
Bernhard O. Palsson University of California, San Diego
Gyun Min Lee
Gyun Min Lee Korea Advanced Institute of Science and Technology
Eric Courchesne
Eric Courchesne University of California, San Diego
Michael V. Lombardo
Michael V. Lombardo Italian Institute of Technology
Dong-Yup Lee
Dong-Yup Lee Sungkyunkwan University
Lars K. Nielsen
Lars K. Nielsen University of Queensland
Jeffrey D. Esko
Jeffrey D. Esko University of California, San Diego
Michael J. Betenbaugh
Michael J. Betenbaugh Johns Hopkins University
Jens Nielsen
Jens Nielsen Chalmers University of Technology
Karen Pierce
Karen Pierce University of California, San Diego

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