Ilia K.
@ilya_ibc
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postdoctoral fellow at Lund University; Omics bioinformatician interested in immunology; ski and hiking fan
Joined September 2012
📢 New in @ImmunityCP: We have mapped the transcription factor “routes” that program two dendritic cell subsets opening paths for personalized #cancer #immunotherapy. Read it here: https://t.co/u4j9xoVhEL Here is a summary of what we discovered 🧵: Illustration by @azuravesta
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Really excited to share our latest preprint, led by @xinniej from the @ArlottaLab and @zhangf Labs (in collaboration with Aviv Regev, @jzlevin, @elisebrobinson, and others), on in vivo Perturb-seq! Thread:
In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with Autism risk genes https://t.co/6enTEFxFBJ
#bioRxiv
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Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains https://t.co/aJhi9KSR35
#bioRxiv
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Or start in @PyTorch with EPFL's deep learning course! https://t.co/a3AaGEG3Bq
If you haven't tried PyTorch now, here's how to get started :)
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Tutorials for pseudotime analysis with Monocle 2/3 (@Xiaojie_Qiu, @HPliner, @coletrapnell) and Slingshot (@drisso1893) using kallisto|bustools pre-processing: https://t.co/6Na0aez7FX.
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Can we predict the single-cell transcriptomic state backward or forward over arbitrary time-scales (under certain reasonable assumptions)? We developed dynamo and show this is plausible by predicting long-term evolution of single cell with scSLAM-seq data. https://t.co/pmFWRp7q43
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9 key CS topics - and the best book and video for learning each of them 🖥 ⌨: https://t.co/i6qNiDQPpT (credit @BradfieldCS) #mondaymotivation
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Pleased to announce the release of our new package Signac today, an extension of Seurat for the analysis of single-cell chromatin data!
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At the Robert Gentleman's 60th Birthday Symposium, Richard Bourgon from @genentech gives a definition of what is a computational biologist: "computational is a modifier, we're biological scientists" #bioc2019
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Back-to-back submission of 2 @humancellatlas sc/snRNAseq Benchmarking Projects: Ding et al. (Levin lab) @broadinstitute
https://t.co/o9eJIo29yG Single-center study (7 methods) Mereu, Lafzi et al. (Heyn lab) @cnag_eu
https://t.co/x8Q92Uj9Ta Multi-center project (13 centers)
biorxiv.org
Single-cell RNA sequencing (scRNA-seq) is the leading technique for charting the molecular properties of individual cells. The latest methods are scalable to thousands of cells, enabling in-depth...
OUT NOW! Proud to present our @humancellatlas paper on "Benchmarking #SingleCell RNA-seq Protocols for Cell Atlas Projects". Testing 13 sc/snRNA-seq methods. Comparative and integrative analysis by @Ati_lz and @elisabetta1412 Big THANKS to @cziscience! https://t.co/x8Q92Uj9Ta
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Several #preprints this year demonstrating chromatin marks and TF mapping in single cells! scDamID&T: https://t.co/xNuKloWBbh scCC : https://t.co/reiJWMuigu CUT&Tag: https://t.co/bNz6ztVjte ACT-seq: https://t.co/4oDq1JKU1A
#genomics #bioinformatics #SingleCell
biorxiv.org
Modern next-generation sequencing-based methods have empowered researchers to assay the epigenetic states of individual cells. Existing techniques for profiling epigenetic marks in single cells often...
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I am very proud to publish my first blog post about deep learning in object detection, which I cover the evolution of important methods in recent years. Enjoy!
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Why Batch Effects Matter in Omics Data, and How to Avoid Them
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Large-scale design of robust #geneticcircuits with multiple inputs and outputs for mammalian cells https://t.co/xDOcGeszD7
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