Dmitry Kobak

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Citations	4883	4631
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Philipp BerensHertie Institute for AI in Brain Health, University of TübingenVerified email at uni-tuebingen.de
Andreas ToliasStanford UniversityVerified email at stanford.edu
Yves BernaertsPostdoc, Champalimaud FoundationVerified email at research.fchampalimaud.org
Cathryn CadwellAssistant Professor, University of California San FranciscoVerified email at ucsf.edu
Christian MachensChampalimaud Neuroscience Programme, Champalimaud FoundationVerified email at neuro.fchampalimaud.org
Xiaolong JiangBaylor College of MedicineVerified email at bcm.edu
Zheng Huan TanBaylor College of MedicineVerified email at bcm.edu
Rickard SandbergProfessor, Karolinska InstitutetVerified email at ki.se
Leonard HartmanisPhD in single-cell genomicsVerified email at ki.se
Dr. Sophie LaturnusCentre of Integrative Neuroscience, University of TübingenVerified email at uni-tuebingen.de
Sergey ShpilkinVerified email at freemoscow.university
Ariel KarlinskyHebrew UniversityVerified email at mail.huji.ac.il
Naoshige UchidaProfessor of Molecular and Cellular Biology, Harvard UniversityVerified email at mcb.harvard.edu
George C. LindermanMassachusetts General HospitalVerified email at mgh.harvard.edu
Maxim S. PshenichnikovUniversity of GroningenVerified email at rug.nl
Christos ConstantinidisStevenson Chair of Biomedical Engineering, Vanderbilt UniversityVerified email at vanderbilt.edu
Jesus Ramon CastroPhD Student, University of MiamiVerified email at miami.edu
Jan Niklas BöhmUniversity of TübingenVerified email at uni-tuebingen.de
Zachary F MainenChampalimaud Neuroscience ProgrammeVerified email at neuro.fchampalimaud.org
ranulfo romoProfesor de Neurociencias, Universidad Nacional Autónoma de MéxicoVerified email at ifc.unam.mx

Dmitry Kobak

University of Tübingen

Verified email at uni-tuebingen.de - Homepage

Machine Learning Unsupervised Learning Manifold learning Transcriptomics Computational Neuroscience


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The art of using t-SNE for single-cell transcriptomics D Kobak, P Berens Nature communications 10 (1), 5416, 2019	985	2019
Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset A Karlinsky, D Kobak elife 10, e69336, 2021	782*	2021
Demixed principal component analysis of neural population data D Kobak, W Brendel, C Constantinidis, CE Feierstein, A Kepecs, ... elife 5, e10989, 2016	544	2016
A multimodal cell census and atlas of the mammalian primary motor cortex Principal manuscript editors, Analysis coordination, ... Nature 598 (7879), 86-102, 2021	350	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	325*	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	290	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	260	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	178	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	136	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	131	2021
Attraction-repulsion spectrum in neighbor embeddings JN Böhm, P Berens, D Kobak Journal of Machine Learning Research 23 (95), 1-32, 2022	96*	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	85	2021
Excess mortality reveals Covid's true toll in Russia D Kobak Significance (Oxford, England) 18 (1), 16, 2021	79	2021
Integer percentages as electoral falsification fingerprints D Kobak, S Shpilkin, MS Pshenichnikov	73	2016
Statistical fingerprints of electoral fraud? D Kobak, S Shpilkin, MS Pshenichnikov Significance 13 (4), 20-23, 2016	62*	2016
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	50*	2020
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	50	2019
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	34*	2020
Sparse reduced-rank regression for exploratory visualisation of paired multivariate data D Kobak, Y Bernaerts, MA Weis, F Scala, AS Tolias, P Berens Journal of the Royal Statistical Society Series C: Applied Statistics 70 (4 …, 2021	32*	2021

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