Nikolay Oskolkov (@NikolayOskolkov)
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NikolayOskolkov

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Top repositories

1

tSNE_vs_UMAP_GlobalStructure

Here we address the global structure preservation by tSNE and UMAP
HTML
47
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2

HowUMAPWorks

Here I explain the math behind UMAP and show how to program it from scratch in Python
HTML
38
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3

DeepLearningSingleCellBiology

Here I show how to use Deep Autoencoders for single cell RNA sequencing data analysis
HTML
19
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4

DeepLearningAncientDNA

Here I show how to use Convolutional Neural Networks (CNNs) for Ancient DNA analysis
HTML
15
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5

ClusteringHighDimensions

Here I demonstrate how to automatically detect the number of clusters in scRNAseq data
R
11
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6

DeepLearningDataIntegration

Here I show how to use Deep Learning for biological and biomedical Data Integration.
Python
11
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7

UMAPDataIntegration

Graph based data integration with UMAP
HTML
10
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8

NormalizeSingleCell

Comparison of single cell normalization strategies
HTML
10
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9

DeepLearningMicrobiome

HTML
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10

LSTMNeanderthalDNA

Implementation of LSTM for detecting regions of Neanderthal introgression in modern human genomes
HTML
9
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11

DimReductSingleCell

Here I cover linear and non-linear dimension reduction techniques for single cell genomics
Python
6
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12

DeepLearningClinicalDiagnostics

Here I show how to utilize Bayesian Deep Learning using PyMC3 for making more accurate and safer predictions for biomedical applications
HTML
5
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13

SupervisedOMICsIntegration

Supervised intehration of CLL data with PLS-DA from DIABLO mixOmics
HTML
5
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14

UnivariteVsMultivariteModels

Here we compare a few multivarite and univarite feature selection models
HTML
4
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15

DeepLearningMicroscopyImaging

Here I demonstrate how to use Faster-RCNN and Mask-RCNN for cell detection using Human Protein Atlas (HPA) digital image data
HTML
3
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16

LMMFromScratch

Deriving and coding Linear Mixed Model (LMM) from scratch
HTML
3
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17

AdvancedPythonCourse

Material for advanced Python course 2019
Jupyter Notebook
3
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18

aMeta

R
3
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19

DeepLearningNeanderthalIntrogression

Here I deposite input files and Jupyter notebooks on detecting Neanderthal introgression analysis
HTML
3
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20

GenomicsNewClothes

Here I discuss common pitfalls in Genetics research due to the high-dimensional nature of genetic variation data that suffers from the Curse of Dimensionality
HTML
3
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21

tSNELargePerplexityLimit

Here we investigate the degradation of tSNE to PCA / MDS at large perplexity values
HTML
2
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22

OsloBioinfoWeek2022

HTML
2
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23

UMAP_VarianceExplained

Here I show a simple way to estimate data variance explained by UMAP and tSNE components
HTML
2
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24

HowToBatchCorrectSingleCell

Here I explain batch-effects correction techniques for scRNAseq experiments
HTML
2
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25

SBW2022

This is a teaching material for scRNAseq workshop within SBW2022
HTML
2
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26

HowToInitializeUMAPtSNE

Checking how tSNE and UMAP depend on different initialization scenarios
R
2
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27

WhyPCALooksTriangular

Here I provide some insights on the peculiar triangular shape of PCA plots that can often be found in Life Science projects
HTML
2
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28

UnsupervisedOMICsIntegration

Multi-OMICs Factor Analysis on scNMT data set
HTML
2
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29

IntegrativeOmicsWorkflow

Here we provide a primer-workflow for biological data integration analysis.
HTML
2
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30

FeatureSelectionIntegrOMICs

How to us univariate and multivariate feature selection for OMICs integration
HTML
1
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31

COVID19

Corona infection related computations
Jupyter Notebook
1
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32

REML

Deriving and coding Linear Mixed Model in Restricted Maximum Likelihood (REML) approach
HTML
1
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33

HowLinearMixedModelWorks

HTML
1
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