Concepedia

Author

David Heckmann

University of California San DiegoORCID

Also Known As

D. Heckmann, David Heckmann, Heckmann, David

32

Publications

1.6K

Citations

15

H-Index

16

Concepts

All Affiliations

University of California San DiegoHeinrich Heine University DüsseldorfTechnical University of DenmarkNovo Nordisk FoundationCluster of Excellence on Plant Sciences
DH

About

David Heckmann is an author at University of California San Diego specializing in plant physiology, photosynthesis, and engineering.

Top Concepts

#ConceptH-IndexPublicationsCitations

1

Engineering

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310

2

Health Sciences

1

1

119

3

Natural Sciences

1

1

191

4

Biology

1

1

191

5

Bioenergetics

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191

David Heckmann

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15

Publications

1.5K

Citations

14

H-Index

YearCitations

Machine learning applied to enzyme turnover numbers reveals protein structural correlates and improves metabolic models

David Heckmann, Colton J. Lloyd, Nathan Mih,

Nature Communications

2018

239

The role of photorespiration during the evolution of C4 photosynthesis in the genus Flaveria

Julia Mallmann, David Heckmann, Andrea Bräutigam,

eLife

2014

221

Predicting C4 Photosynthesis Evolution: Modular, Individually Adaptive Steps on a Mount Fuji Fitness Landscape

David Heckmann, Stefanie Schulze, Alisandra K. Denton,

Cell

2013

191

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance

Erol Kavvas, Edward Catoiu, Nathan Mih,

Nature Communications

2018

182

Cellular responses to reactive oxygen species are predicted from molecular mechanisms

Laurence Yang, Nathan Mih, Amitesh Anand,

Proceedings of the National Academy of Sciences

2019

125

Deep learning allows genome-scale prediction of Michaelis constants from structural features

Alexander Kroll, Martin K. M. Engqvist, David Heckmann,

PLoS Biology

2021

124

Machine Learning Techniques for Predicting Crop Photosynthetic Capacity from Leaf Reflectance Spectra

David Heckmann, Urte Schlüter, Andreas P.M. Weber

Molecular Plant

2017

119

Kinetic profiling of metabolic specialists demonstrates stability and consistency of in vivo enzyme turnover numbers

David Heckmann, Anaamika Campeau, Colton J. Lloyd,

Proceedings of the National Academy of Sciences

2020

87

A biochemically-interpretable machine learning classifier for microbial GWAS

Erol Kavvas, Laurence Yang, Jonathan M. Monk,

Nature Communications

2020

82

Independent component analysis recovers consistent regulatory signals from disparate datasets

Anand V. Sastry, Alyssa Hu, David Heckmann,

PLoS Computational Biology

2021

43

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