142 Open source projects that are alternatives of or similar to dbMAP

Streaming, Memory-Limited, r-truncated SVD Revisited!

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R package (compatible with SCope) to create generic .loom files and extend them with other data e.g.: SCENIC regulons, Seurat clusters and markers, ...

Multiome GRN inference.

Graph-linked unified embedding for single-cell multi-omics data integration

🐟 🔬🦀 alevin-fry is an efficient and flexible tool for processing single-cell sequencing data, currently focused on single-cell transcriptomics and feature barcoding.

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No description or website provided.

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Mathematical & Statistical topics to perform statistical analysis and tests; Linear Regression, Probability Theory, Monte Carlo Simulation, Statistical Sampling, Bootstrapping, Dimensionality reduction techniques (PCA, FA, CCA), Imputation techniques, Statistical Tests (Kolmogorov Smirnov), Robust Estimators (FastMCD) and more in Python and R.

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Aydin — User-friendly, Fast, Self-Supervised Image Denoising for All.

This is the source code of PMHLD-Patch-Map-Based-Hybrid-Learning-DehazeNet-for-Single-Image-Haze-Removal which has been accepted by IEEE Transaction on Image Processing 2020.

Simulating single-cell data using gene regulatory networks 📠

🔧🧠 MEEGkit: MEG & EEG processing toolkit in Python 🧠🔧

Fast visualization tool for large-scale and high dimensional single-cell data

kNN-based next-basket recommendation

Software for exploration of gene expression data from single-cell RNA sequencing.

A Uniform Manifold Approximation and Projection (UMAP) library for Java, developed by Tag.bio in collaboration with Real Time Genomics.

R package to do the Ligand Receptor Analysis Visualization

Expression Weighted Celltype Enrichment. See the package website for up-to-date instructions on usage.

Clone identification from single-cell data

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A curated list of awesome Speech Enhancement papers, libraries, datasets, and other resources.

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Online feature-extraction and classification algorithm that learns representations of input patterns.

💡 💾 💽 A simple, intuitive and Efficient single cell binary Data Storage format

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

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spatial transcriptome, single cell

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Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST