Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks

b) Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks. (Nature communication, 2020). https://t.co/znWSZEX9lq.

b) Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks. (Nature communication, 2020). https://t.co/znWSZEX9lq.

RT @biorxiv_pubd: Realistic in silico generation and augmentation of single cell RNA-seq data using Generative Adversarial Neural Networks…

Realistic in silico generation and augmentation of single cell RNA-seq data using Generative Adversarial Neural Networks published as: https://t.co/5k8LDPvvgI @naturecomms #biorxiv

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/GlbqtPNeXv

RT @LibKot: Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/…

RT @LibKot: Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/…

I wonder whether in silico generation or augmentation of scRNASeq 'replicates' (through the use of GANs as an example: https://t.co/BdHeaVSZat) would take more biological variation into account and safeguard against false discovery bias

Know I'm late to the party with this, but it would be really interesting to see if augmented data in this manner improves the performance of network inference methods - could be very useful if so

Thank's to GAN this might turn into a real nightmare: https://t.co/2tNi7Tnaqc

RT @RoyalVoxPost: #Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach co…

RT @RoyalVoxPost: #Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach co…

RT @RoyalVoxPost: #Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach co…

RT @RoyalVoxPost: #Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach co…

RT @MachartPierre: Our scGAN paper is out in Nature Communications! We use GANs to generate single-cell RNA-seq for data augmentation and s…

The final version of our cscGAN paper just came out in Nature Communications https://t.co/NR6OdUxx0J

Congratulations Authors! #scGAN paper is online @NatureComms

Endlich!!!!! #scGAN paper is online @NatureComms Congrats all!!! #deeplearning #scRNAseq https://t.co/lhnKKjlTG0

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/jNZk5RiXRE https://t.co/WrgaQwHSHx

Great work. Excited to give this a shot. https://t.co/1mtbyO5IGk

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/3vfoNIACfI https://t.co/V3jkIWJloB

Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/Z9vMWN260G #oncology #scRNAseq #AI #machinelearning

Atheist Science develops Deep Learning tools to generate realistic cells of defined types. Could help compensate the low number of observations available in biomedical research and limit animal experimentation #Miracles #EmpireOfAtheism #AtheistMagic #NWO

"Realistic in silico generation and augmentation of single-cell RNA-seq data using generative adversarial networks https://t.co/OnTA1TK93q " https://t.co/b48G0Z5Lan

Single cell #RNAseq data: https://t.co/h5vHanPf1T

RT @RoyalVoxPost: #Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach co…

RT @RoyalVoxPost: #Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach co…

#Biomedicine: scientists have developed #DeepLearning tools to generate realistic cells of defined types. The approach could help compensate the low number of observations available in biomedical research and limit human/animal experimentation https://t.co

RT @MachartPierre: Our scGAN paper is out in Nature Communications! We use GANs to generate single-cell RNA-seq for data augmentation and s…

Our scGAN paper is out in Nature Communications! We use GANs to generate single-cell RNA-seq for data augmentation and show it improves the quality of the results obtained by several downstream analyses. It's only the prelude to more results coming soon!