Discover and read the best of Twitter Threads about #Transcriptomics
Most recents (8)
The science of #immunotherapy can cure a patient's otherwise incurable cancer.
But sometimes immunotherapy fails completely
Shockingly, we hardly know why.
A meta-analysis of #Genomics & #Transcriptomics in >1,000 immunotherapy-treated patients aims to better understand why🧵
But sometimes immunotherapy fails completely
Shockingly, we hardly know why.
A meta-analysis of #Genomics & #Transcriptomics in >1,000 immunotherapy-treated patients aims to better understand why🧵
This 2021 @CellCellPress paper is one of the best #DataScience #Bioinformatics resources out there for understanding the genetic determinants of response to immune checkpoint inhibitors (ICIs).
cell.com/cell/fulltext/…
cell.com/cell/fulltext/…
Some context:
PD-1 & PD-L1 inhibitors are examples of ICIs.
ICI is a type of immunotherapy that un-blocks the immune system & allows it to mount attacks🤺
It does it by inhibiting checkpoints (s.a. PD-1 & PD-L1): proteins that keep the immune system from attacking its own self
PD-1 & PD-L1 inhibitors are examples of ICIs.
ICI is a type of immunotherapy that un-blocks the immune system & allows it to mount attacks🤺
It does it by inhibiting checkpoints (s.a. PD-1 & PD-L1): proteins that keep the immune system from attacking its own self
🚨Exciting pre-print from the lab!👉"Pervasive evolution of tissue-specificity of ancestral genes differentially shaped vertebrates and insects". Deep comparative #transcriptomics across #bilateria by @FedeMantica et al @CRGenomica. 👀biorxiv.org/content/10.110…. Summary👇
How has tissue-specific gene expression evolved since the origin of bilaterian animals all the way to extant vertebrates and insects? To address this, we assembled a vast RNA-seq dataset covering 8 tissues and 20 species, generating 95 new RNA-seq samples for 15 species. 1/16
Importantly, our study was entirely designed around a symmetric #phylogeny for the vertebrate and insect branches, allowing us to identify ancestral features but also parallel, convergent and divergent evolutionary trajectories between and within the two bilaterian lineages. 2/16
#GraphNeuralNetworks are way too cool to be left unexplored!
In a nutshell, GNNs are an exciting merger between graph theory (math) & #DeepLearning (coding).
Here's my detailed resource stack of best GNN theory explainers, videos & coding tutorials I used for my own learning.
In a nutshell, GNNs are an exciting merger between graph theory (math) & #DeepLearning (coding).
Here's my detailed resource stack of best GNN theory explainers, videos & coding tutorials I used for my own learning.
1. This is a great place to start if you either: want to learn the basics, or enjoy reading about basic concepts explained in a well structured way.
It walks us through graphs in real world, what graphs & GNNs consist of, and how GNNs do prediction.
distill.pub/2021/gnn-intro/
It walks us through graphs in real world, what graphs & GNNs consist of, and how GNNs do prediction.
distill.pub/2021/gnn-intro/
2. Further, this next tutorial walks us through graphs & GNNs in an intuitive manner, while also going quite deep into the specific mathematical terminology of the field.
I like this one a lot because it also includes hands-on PyTorch code at every step.
theaisummer.com/graph-convolut…
I like this one a lot because it also includes hands-on PyTorch code at every step.
theaisummer.com/graph-convolut…
Daily Bookmarks to GAVNet 09/26/2021 greeneracresvaluenetwork.wordpress.com/2021/09/26/dai…
Peznt Journalist on Twitter and ThreadReader
threadreaderapp.com/thread/1440783…
#FutureTrends #predictions #WorldEconomicForum #control #power
threadreaderapp.com/thread/1440783…
#FutureTrends #predictions #WorldEconomicForum #control #power
Single-cell proteomics takes centre stage
nature.com/articles/d4158…
#proteomics #SingleCells #transcriptomics
nature.com/articles/d4158…
#proteomics #SingleCells #transcriptomics
Excited to see my first co-first author paper of my PhD out in @NatureComms! Tweetorial:
In 2016 the Schwartz Lab @UWMDI_UWMed showed a single injection of FGF1 into the brain can permanently revert #Type2Diabetes in @justsaysinmice. We @tunepers lab asked: HOW? (1/9)
In 2016 the Schwartz Lab @UWMDI_UWMed showed a single injection of FGF1 into the brain can permanently revert #Type2Diabetes in @justsaysinmice. We @tunepers lab asked: HOW? (1/9)
With the wet-lab superstar @mariebentsen, we replicated this experiment, but this time, collected hypothalami from these mice at several timepoints following drug injection for #singlecell #transcriptomics with @10xGenomics (2/9)
Our computational analyses found that FGF1 induced massive changes to non-neuronal cells, specifically tanycytes and astrocytes in the first week. Inspired by work from @LiddelowSA on glial reactivity, we asked if FGF1 induced an A2 or A1 state in astrocytes (3/9)
📢🎉The work of #Bat1K is featured on the cover in the latest issue of @nature: “Six reference-quality #genomes reveal evolution of #bat adaptations” 🦇🧬 #bats Our thread 👇 on the paper:nature.com/articles/s4158… 📸: Olivier Farcy(1/n)
📢Have you ever wondered how 🦇 manage to do what they do? #bats have extraordinary adaptations, including powered #flight, laryngeal #echolocation, #vocal #learning and an exceptional #longevity with unique #immunity and resistance to #cancer! 📸: @DanielWhitby5 (2/n)
A #Bat1K team led by @Sonja_Vernes @EmmaTeeling1 @hillermich @TheGeneMyers has just published the raw genetic material that codes for these unique 🦇 adaptations and #superpowers in @nature! #bats #genomics #cool! (3/n)
Time to catch up on some #Senescence papers, starting with beautiful work by @corina_amor_MD, Judith Freucht & @JosefLeibold. They used #CART #CellTherapy to clear #Senescent cells, and you'll never guess what happened next! nature.com/articles/s4158…
Just kidding, you guessed it: disease model mice got better. Props to the authors for A) inducing #Senescence in 3 different ways, B) using 2 models of #NASH/liver #Fibrosis, and C) validating their senescence observations in human samples of #Cancer and #Atherosclerosis.
The linchpin of the paper was identifying a specific membrane marker on #Senescent cells, uPAR. They used bulk #Transcriptomics to identify candidates, then narrowed down with #Proteomic data. Go #Omics!
They didn't explore whether uPAR is causative for the #Senescent phenotype.
They didn't explore whether uPAR is causative for the #Senescent phenotype.
A true gem among #multiomics preprints: Integrative Network Fusion by @MarcoChierici, @nicole_bussola, @viperale, et al:
âś“ 3 TCGA cancers & simulated data
âś“ cross-validation described in detail
âś“ flow diagram
âś“ source code & data shared
âś“ packages w/ version, cited
/n
âś“ 3 TCGA cancers & simulated data
âś“ cross-validation described in detail
âś“ flow diagram
âś“ source code & data shared
âś“ packages w/ version, cited
/n
- [the method description & comments follows]
- link: biorxiv.org/content/10.110…
- licence the above figures/tables: CC BY-NC-ND 4.0
- an earlier version of INF was previously presented in 2018: doi.org/10.1186/s13062…
- this is the first tweet in #SundayMultiOmics series
- link: biorxiv.org/content/10.110…
- licence the above figures/tables: CC BY-NC-ND 4.0
- an earlier version of INF was previously presented in 2018: doi.org/10.1186/s13062…
- this is the first tweet in #SundayMultiOmics series
[[Introduction]]: Similarity network fusion (SNF, doi.org/10.1038/nmeth.…) is a popular technique (600+ citations, a lot for multi-omics!) for getting a sort of consensus signal from multiple omics; it requires the same patients (less commonly - observations) in each omic.
