Dmitry Kobak

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Philipp BerensHertie Institute for AI in Brain Health, University of TübingenE-mail confirmado em uni-tuebingen.de
Andreas ToliasStanford UniversityE-mail confirmado em stanford.edu
Yves BernaertsPostdoc, Champalimaud FoundationE-mail confirmado em research.fchampalimaud.org
Cathryn CadwellAssistant Professor, University of California San FranciscoE-mail confirmado em ucsf.edu
Ariel KarlinskyHebrew UniversityE-mail confirmado em mail.huji.ac.il
Christian MachensChampalimaud Neuroscience Programme, Champalimaud FoundationE-mail confirmado em neuro.fchampalimaud.org
Xiaolong JiangBaylor College of MedicineE-mail confirmado em bcm.edu
Zheng Huan TanBaylor College of MedicineE-mail confirmado em bcm.edu
Rickard SandbergProfessor, Karolinska InstitutetE-mail confirmado em ki.se
Leonard HartmanisPhD in single-cell genomicsE-mail confirmado em ki.se
Sergey ShpilkinE-mail confirmado em freemoscow.university
Dr. Sophie LaturnusCentre of Integrative Neuroscience, University of TübingenE-mail confirmado em uni-tuebingen.de
Naoshige UchidaProfessor of Molecular and Cellular Biology, Harvard UniversityE-mail confirmado em mcb.harvard.edu
George C. LindermanMassachusetts General HospitalE-mail confirmado em mgh.harvard.edu
Jan Niklas BöhmUniversity of TübingenE-mail confirmado em uni-tuebingen.de
Christos ConstantinidisStevenson Chair of Biomedical Engineering, Vanderbilt UniversityE-mail confirmado em vanderbilt.edu
Maxim S. PshenichnikovUniversity of GroningenE-mail confirmado em rug.nl
Jesus Ramon CastroPhD Student, University of MiamiE-mail confirmado em miami.edu
Zachary F MainenChampalimaud Neuroscience ProgrammeE-mail confirmado em neuro.fchampalimaud.org
ranulfo romoProfesor de Neurociencias, Universidad Nacional Autónoma de MéxicoE-mail confirmado em ifc.unam.mx

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Dmitry Kobak

University of Tübingen

E-mail confirmado em uni-tuebingen.de - Página inicial

Machine Learning Unsupervised Learning Manifold learning Transcriptomics Computational Neuroscience


Título Ordenar por citações Ordenar por ano Ordenar por título	Citado por Citado por	Ano
The art of using t-SNE for single-cell transcriptomics D Kobak, P Berens Nature Communications 10 (1), 5416, 2019	1039	2019
Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset A Karlinsky, D Kobak eLife 10, e69336, 2021	810*	2021
Demixed principal component analysis of neural population data D Kobak, W Brendel, C Constantinidis, CE Feierstein, A Kepecs, ... eLife 5, e10989, 2016	566	2016
A multimodal cell census and atlas of the mammalian primary motor cortex Principal manuscript editors, Analysis coordination, ... Nature 598 (7879), 86-102, 2021	378	2021
Initialization is critical for preserving global data structure in both t-SNE and UMAP D Kobak, GC Linderman Nature Biotechnology 39 (2), 156-157, 2021	358*	2021
Phenotypic variation of transcriptomic cell types in mouse motor cortex F Scala, D Kobak, M Bernabucci, Y Bernaerts, CR Cadwell, JR Castro, ... Nature 598 (7879), 144-150, 2021	308	2021
Distributed and mixed information in monosynaptic inputs to dopamine neurons J Tian, R Huang, JY Cohen, F Osakada, D Kobak, CK Machens, ... Neuron 91 (6), 1374-1389, 2016	265	2016
Layer 4 of mouse neocortex differs in cell types and circuit organization between sensory areas F Scala, D Kobak, S Shan, Y Bernaerts, S Laturnus, CR Cadwell, ... Nature Communications 10 (1), 1-12, 2019	192	2019
The optimal ridge penalty for real-world high-dimensional data can be zero or negative due to the implicit ridge regularization D Kobak, J Lomond, B Sanchez Journal of Machine Learning Research 21 (169), 1-16, 2020	147	2020
Analytic Pearson residuals for normalization of single-cell RNA-seq UMI data J Lause, P Berens, D Kobak Genome Biology 22, 1-20, 2021	145	2021
Attraction-repulsion spectrum in neighbor embeddings JN Böhm, P Berens, D Kobak Journal of Machine Learning Research 23 (95), 1-32, 2022	102*	2022
Patch-seq: Past, present, and future M Lipovsek, C Bardy, CR Cadwell, K Hadley, D Kobak, SJ Tripathy Journal of Neuroscience 41 (5), 937-946, 2021	94	2021
Excess mortality reveals Covid's true toll in Russia D Kobak Significance 18 (1), 16, 2021	80	2021
Integer percentages as electoral falsification fingerprints D Kobak, S Shpilkin, MS Pshenichnikov The Annals of Applied Statistics 10 (1), 54-73, 2016	71	2016
Statistical fingerprints of electoral fraud? D Kobak, S Shpilkin, MS Pshenichnikov Significance 13 (4), 20-23, 2016	60*	2016
Heavy-tailed kernels reveal a finer cluster structure in t-SNE visualisations D Kobak, G Linderman, S Steinerberger, Y Kluger, P Berens Joint European Conference on Machine Learning and Knowledge Discovery in …, 2019	55	2019
Cell type composition and circuit organization of clonally related excitatory neurons in the juvenile mouse neocortex CR Cadwell, F Scala, PG Fahey, D Kobak, S Mulherkar, FH Sinz, ... eLife 9, e52951, 2020	51*	2020
Statistical anomalies in 2011-2012 Russian elections revealed by 2D correlation analysis D Kobak, S Shpilkin, MS Pshenichnikov arXiv preprint arXiv:1205.0741, 2012	50*	2012
A systematic evaluation of interneuron morphology representations for cell type discrimination S Laturnus, D Kobak, P Berens Neuroinformatics 18, 591-609, 2020	36	2020
The landscape of biomedical research R González-Márquez, L Schmidt, BM Schmidt, P Berens, D Kobak Patterns 5 (6), 2024	33	2024

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