Author

David Hofmann

Emory University

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

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Biology Disciplines

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Neuroscience· 2 Bioinformatics· 1

Signature Assays, Organisms & Methods

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Research Focus:differential expression· 2 Assay:electronic health records· 2 Approach:statistical model· 2 Approach:benchmark study· 1 Research Focus:benchmarking· 1 Approach:deep learning· 1 Research Focus:dimensionality reduction· 1 Approach:experimental assay· 1

Frequent Co-Authors

Andreas NeefiD· 1 shared Chenfei ZhangiD· 1 shared Chethan PandarinathiD· 1 shared Cristiano AlessandroiD· 1 shared Damián G. HernándeziD· 1 shared Fred WolfiD· 1 shared Ilya M. NemenmaniD· 1 shared Jonas BrauniD· 1 shared

Activity by Year

2017-2022 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 12 mutual co-author links

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1 shared paperNeuroscience

Andreas NeefORCID

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Author profile →

3 papers

Recent·Most cited

Estimating muscle activation from EMG using deep learning-based dynamical systems models

Lahiru N. Wimalasena, Jonas Braun, Mohammad Reza Keshtkaran, David Hofmann, Juan Álvaro Gallego, Cristiano Alessandro, Matthew C. Tresch, Lee E. Miller, Chethan Pandarinath

This paper uses a deep learning model to estimate muscle activation from EMG signals, showing improved performance over traditional methods in predicting joint kinematics and force.

Journal of Neural Engineering · Apr 2, 2022Peer-reviewedNeuroscience

Ultrafast population coding and axo-somatic compartmentalization

Chenfei Zhang, David Hofmann, Andreas Neef, Fred Wolf

The paper investigates how axonal ion channel properties affect ultrafast population coding in cortical neurons, finding that voltage sensitivity, not quantity or location, determines coding speed and high-frequency response.

PLoS Computational Biology · Jan 18, 2022Peer-reviewedNeuroscience

Reverse-Engineering Biological Networks From Large Data Sets

Joseph L. Natale, David Hofmann, Damián G. Hernández, Ilya M. Nemenman

This paper reviews the field of reverse-engineering biological networks, discussing methodologies, applications, and the justification for large-scale computational approaches in systems biology.

bioRxiv · May 28, 2017 · PreprintBioinformatics