Author

Daniel R. Kepple

Cold Spring Harbor Laboratory

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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Neuroscience· 3

Signature Assays, Organisms & Methods

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Assay:electronic health records· 2 Organism:mouse· 2 Approach:statistical model· 2 Research Focus:cell type annotation· 1 Approach:deep learning· 1 Research Focus:differential expression· 1 Research Focus:dimensionality reduction· 1 Approach:variational autoencoder· 1

Frequent Co-Authors

Alexei A. KoulakoviD· 3 shared Brittany N. CazakoffiD· 1 shared Dennis EckmeieriD· 1 shared Dinu Florin AlbeanuiD· 1 shared Heike S. Demmer· 1 shared Honggoo Chae· 1 shared Ngoc Tran· 1 shared Sergey A. ShuvaeviD· 1 shared

Activity by Year

2018-2019 · peak 2/yr

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10 top collaborators · 19 mutual co-author links

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3 shared papersNeuroscience

Alexei A. KoulakovORCID

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3 papers

Recent·Most cited

Mosaic representations of odors in the input and output layers of the mouse olfactory bulb

Honggoo Chae, Daniel R. Kepple, Walter Germán Bast, Venkatesh N. Murthy, Alexei A. Koulakov, Dinu Florin Albeanu

The paper examines how odor features are represented in the input and output layers of the mouse olfactory bulb, finding that physical-chemical descriptors poorly predict neuronal representations.

Nature Neuroscience · Jul 22, 2019Peer-reviewedNeuroscience

DeepNose: Using artificial neural networks to represent the space of odorants

Ngoc Tran, Daniel R. Kepple, Sergey A. Shuvaev, Alexei A. Koulakov

This paper trains an autoencoder to represent odorant chemical space and uses it to predict human olfactory percepts with accuracy comparable to traditional molecular descriptors.

bioRxiv · Nov 7, 2018 · PreprintNeuroscience

Computational algorithms and neural circuitry for compressed sensing in the mammalian main olfactory bulb

Daniel R. Kepple, Brittany N. Cazakoff, Heike S. Demmer, Dennis Eckmeier, Stephen D. Shea, Alexei A. Koulakov

The paper proposes a compressed sensing algorithm in the mammalian main olfactory bulb using computational modeling and electrophysiological data, showing it can efficiently represent odors and adapt to odor mixtures.

bioRxiv · Jun 5, 2018 · PreprintNeuroscience