Collaborative PhD with @BenLehner and @GenomeDataLab; playing around with tons of mutations, RNA and translation
Barcelona
Joined July 2022
- Tweets52
- Following449
- Followers150
- Likes185
Pinned Tweet
A much improved version of this, today out in @NatureGenet ! with @BenLehner and @FranSupek nature.com/articles/s41588-0…
Time to share my PhD work where we quantified the translational readthrough of thousands of pathogenic stop codons and trained predictive models to predict drug-induced readthrough of any stop codon. With the priceless guidance from @FranSupek +@BenLehner! biorxiv.org/content/10.1101/…
Ignasi Toledano retweeted
At @ALLOXbio we now have 3 computational positions available!
📌Structural Bioinformatics Scientist 👉 tinyurl.com/3rs46j4t
📌Platform Bioinformatician 👉 tinyurl.com/nyvazbke
📌Computational Chemist 👉 tinyurl.com/5n6vpem3
Apply or repost to help us spread the word 🙏
Ignasi Toledano retweeted
🔥PhD student & postdoc opportunity @GenomeDataLab!
Are you keen on:
- driving cutting-edge science @ interface of #AI and cancer #genomics?
- working in a dynamic & supportive environment of @UCPH_BRIC?
- joining the U of Copenhagen, top-3 ranked uni in EU?
Apply below👇
Ignasi Toledano retweeted
The genetic architecture of protein stability
by @aj4re @ainamartiaranda @cristonah @ToniBeltran13 @JoernSchmiedel
nature.com/articles/s41586-0…
@CRGenomica @sangerinstitute @ALLOXbio
Ignasi Toledano retweeted
We report many proteins not predicted by the genetic code.
They are stable & abundant O( 10³ ) copies / cell.
Generative mechanisms include codon-anticodon mismatches & RNA modifications.
Their abundance depends on codon frequency & protein stability.
biorxiv.org/content/10.1101/…
Ignasi Toledano retweeted
Investigadors catalans desenvolupen un algoritme "detectiu" per predir els millors fàrmacs contra trastorns greus, com malalties degeneratives i alguns tipus de càncer ccma.cat/324/desenvolupen-un… ccma.cat/324/desenvolupen-un…
Ignasi Toledano retweeted
(1/2) The #BISTIgnite Programme is open for applications!
An opportunity for #BISTCommunity researchers & postdocs to Ignite new interdisciplinary research collaborations
No preliminary results are needed in the seed phase, just an idea + a team
bist.eu/research/ignite/
Ignasi Toledano retweeted
Thrilled to announce we just got funded by @novonordiskfond Research Leader program!! We will explore the mechanisms behind islet cell maturation using human pluripotent stem cells. Recruiting PostDocs and PhD students really soon, get in touch ;) @STEMMProgram @helsinkiuni
Ignasi Toledano retweeted
Introducing the Domainome... Site saturation mutagenesis of 500 human protein domains reveals the contribution of protein destabilization to genetic disease by @ToniBeltran13 @CRGenomica @sangerinstitute @BGI_Genomics biorxiv.org/content/10.1101/…
Ignasi Toledano retweeted
Our randomisation of hydrophobic protein cores is out @bioRxiv! With Gesa Voigt, @aj4re and @BenLehner we learned that pervasive allostery constrains evolution beyond stability and that this is indeed simple to model despite limited epistasis we identify biorxiv.org/content/10.1101/…
Ignasi Toledano retweeted
I’m super happy to finally share what I have been up to the last few years at the @BenLehner lab in Barcelona! We made lots of double mutants on the kinase domain of Src to study allosteric communication.
The allosteric landscape of the Src kinase. Amazing work from @ToniBeltran13 with @aj4re biorxiv.org/content/10.1101/… @CRGenomica @sangerinstitute
Ignasi Toledano retweeted
Honored to be among the recipients of the NWO Open Competition M1 grant! We will develop tools to improve our understanding of TCR-antigen interactions, using high-throughput screening & AI. Stay tuned for a postdoc vacancy to join this exciting project!
nwo.nl/en/news/nineteen-inno…
Ignasi Toledano retweeted
Just out in Nature Communications. Great finish to Kotcha's thesis work and extremely productive collaboration with Bedwell lab at UAB! We define cis-acting sequences regulating translation termination & accurately predict readthrough efficiency of multiple CFTR nonsense alleles.
Ignasi Toledano retweeted
Excited to share my PhD journey exploring NMD efficiency's variability across tumors, tissues and individuals.
Link:
biorxiv.org/content/10.1101/…
A big thank you to @FranSupek and the awesome lab @GenomeDataLab at @IRBBarcelona
1/7🧵👇
Ignasi Toledano retweeted
What if we could build complete maps of allosteric sites for entire proteins? Now we can. Super excited to see this heroic effort by @WengChenchun @BenLehner @AlbertIltirda finally published. nature.com/articles/s41586-0…
Ignasi Toledano retweeted
🇩🇰My lab at @UCPH_BRIC Uni of Copenhagen, Denmark is recruiting
💻 #bioinformatics and ⚗ wet-lab #postdocs and 🧑🔬#research assistants
Cancer evolution, genome instability, artificial intelligence for DNA analysis. #ERC & NNF projects
👇Positions listed below. Please RT! (RX?)
Ignasi Toledano retweeted
Extremely simple biophysical models do surprisingly good genetic prediction in sequence spaces >10^10, suggesting that vogue deep learning models may be unnecessarily complex. New work + scientific debut for Aina Martí-Aranda w/ @cristonah & @BenLehner
biorxiv.org/content/10.1101/…
Ignasi Toledano retweeted
Excited to finally share some of my PhD work on quantifying the effects of indel mutations on protein stability and function using deep mutational scanning. From sunny @CRGenomica together with @ToniBeltran13 and guidance from @BenLehner
biorxiv.org/content/10.1101/…
Ignasi Toledano retweeted
New chapter in our ongoing RNA Review Series:
@JavierFCaceres1 et al discuss #mRNA quality control mechanisms including non-stop and no-go mRNA decay pathways and the nonsense-mediated mRNA decay pathway
Translation-coupled mRNA quality control mechanisms
embopress.org/doi/full/10.15…
Time to share my PhD work where we quantified the translational readthrough of thousands of pathogenic stop codons and trained predictive models to predict drug-induced readthrough of any stop codon. With the priceless guidance from @FranSupek +@BenLehner! biorxiv.org/content/10.1101/…
We are very excited for the potential role that our datasets and models can have on patient stratification on the upcoming clinical trials. Selecting the correct group of patients is likely to boost the success of clinical trials and accelerate drug implementation into clinics.
Together with these two must-read studies doi.org/10.1038/s41586-023-0… and doi.org/10.1016/j.cell.2023.…, a very exciting year for the readthrough field!
