Discover NikolayOskolkov/DeepLearningMicroscopyImaging Open Source

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Created over 5 years ago
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NikolayOskolkov

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

tSNE_vs_UMAP_GlobalStructure

Here we address the global structure preservation by tSNE and UMAP

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HowUMAPWorks

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

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DeepLearningSingleCellBiology

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

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DeepLearningAncientDNA

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

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ClusteringHighDimensions

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

DeepLearningDataIntegration

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

Python

UMAPDataIntegration

Graph based data integration with UMAP

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NormalizeSingleCell

Comparison of single cell normalization strategies

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DeepLearningMicrobiome

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LSTMNeanderthalDNA

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

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DimReductSingleCell

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

Python

DeepLearningClinicalDiagnostics

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

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SupervisedOMICsIntegration

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

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UnivariteVsMultivariteModels

Here we compare a few multivarite and univarite feature selection models

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LMMFromScratch

Deriving and coding Linear Mixed Model (LMM) from scratch

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AdvancedPythonCourse

Material for advanced Python course 2019

Jupyter Notebook

aMeta

DeepLearningNeanderthalIntrogression

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

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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

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tSNELargePerplexityLimit

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

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OsloBioinfoWeek2022

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UMAP_VarianceExplained

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

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HowToBatchCorrectSingleCell

Here I explain batch-effects correction techniques for scRNAseq experiments

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SBW2022

This is a teaching material for scRNAseq workshop within SBW2022

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HowToInitializeUMAPtSNE

Checking how tSNE and UMAP depend on different initialization scenarios

WhyPCALooksTriangular

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

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UnsupervisedOMICsIntegration

Multi-OMICs Factor Analysis on scNMT data set

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IntegrativeOmicsWorkflow

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

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FeatureSelectionIntegrOMICs

How to us univariate and multivariate feature selection for OMICs integration

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COVID19

Corona infection related computations

Jupyter Notebook

REML

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

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HowLinearMixedModelWorks

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NikolayOskolkov/DeepLearningMicroscopyImaging

NikolayOskolkov

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