Please note I assume there have not been many changes or additions to these resubmission given that they were already loved and got high impact evaluations - BUT if you substantially changed the application in between submissions please write that in the Notes..
If your grant does not have percentiles but only Impact Scores, please input those instead. All we need is a way to see how consistent/inconsistent these scores are, for the first time, unfortunately, for "funded" grants. Feel free to share the Google Doc link in other platforms or here.
All entries will be anonymous and only for aggregate analysis, share your name if you like, use an alias of some sort that you can later track and edit, if not. You can also message your scores to me. Whatever info you feel comfortable sharing. Also vent off, if you like! We all need it sometimes.
I thought we could gather them somewhere and see for ourselves the level of variability and "chance" factor in getting NIH funding. Three reviewers loved your grant, great (great if you got it funded, of course) ! Would another three like it the same way in the next cycle!
I hope NIH will properly gather these statistics and share at some point but not holding my breath for anytime soon. The idea is to look at the destiny of grants that would have been funded in normal years but did not in 2025. Now that most of us resubmitted them and are getting "new" scores
Let's have a reality check about NIH/science finding! We all know variability in grant reviews is real. BUT we DID NOT have a way to test what would happen to a "funded" grant if it was reviewed again. IF you had a grant that would have made it but did not (2025!) ➡️ docs.google.com/spreadsheets...
What a wonderful paper! Congrats
To accommodate decision timelines from RECOMB main conference and ISMB, we have now extended the submission deadline with RECOMB-RSG to March 13th, there will be no more extensions. Looking forward to have you join us in Greece!
recomb-rsg.github.io
2 PhD candidates in my group: Michal @malszycki.bsky.social and Lisa led this work. We are very thankful to Ay lab ( @ferhatay.bsky.social ) and Alev lab (ASHBi, Kyoto), who helped make our story more complete. This work was funded by @dfg.de in the framework of @spp2202.bsky.social
Analysis of the evolution of this gene architecture and the presence of GC-rich isochores revealed that these features are specific to amniotes. By using the pA-RNA signal as a proxy for speckles we show the speckles are present in amniotes and absent in fish and invertebrates.
The short & GC-rich introns emerged in amniotes and were once long and GC-poor (in fish). The emergence of this gene architecture coincides with the expansion of SON’s IDRs. IDRs of SON are necessary and sufficient to form functional speckles.
Problems in splicing, due to SF3 complex dispersal, cause changes in gene expression, but only a small set of exons-introns are sensitive to speckles loss. These genes have introns with short & GC-rich architecture and are found in GC-rich isochores.
Differential gene expression analysis upon speckles loss reveals only genes within high GC chromatin domains are susceptible. The distance of the chromosomes 18 (lowest GC content) and 19 (highest GC content) from the speckles also indicate their speckle dependency.
Speckles take a large space in the human cell nucleus and form viscoelastic boundaries that restrict random chromatin movements. Upon speckles loss, the chromatin mobility increases and active(A) and inactive(B) chromatin compartments mix as shown by the Pore-C analysis by @ferhatay.bsky.social lab
Nuclear speckles are protein and RNA rich condensates that are proximal to GC-rich regions of the human genome. We dissolved speckles by rapidly depleting the 2 core proteins; SON & SRRM2 and investigated the role of speckles in: 1. 3D genome folding 2. transcription & splicing.
Our most recent work on the “function and evolution” of #nuclear-speckles is now online at Cell @cp-cell.bsky.social
doi.org/10.1016/j.ce...
Read the thread👇 for the highlights of our findings.
Thanks to
@ferhatay.bsky.social
and Aly Khan, we’re excited to announce a new chapter for RECOMB-RSG 2026. After years with ISCB/DREAM, we are transitioning to an official RECOMB satellite meeting (May 25 in Thessaloniki). recomb-rsg.github.io
From RIME to reason
In this Research Letter by Hal M. Hoffman @ferhatay.bsky.social & team, scRNA-seq analysis before & after treatment of recurrent infectious mucocutaneous eruption (RIME) reveals dysregulation of TNF/IFN signaling & classical monocytes: doi.org/10.1172/jci....
It did fly! Happy new year Jiao, thank you!
10th year anniversary of Ay lab at LJI! What a journey so far! Thank you to all lab members, collaborators, LJI family, who made this enjoyable and exciting. Here is a photo that summarizes how my lab sees me now 😂😂😢😢
Happy to see this out @insight.jci.org The first paper of hopefully many with Reid Oldenburg, Croker lab and others at UCSD utilizing BD Rhapsody platform for single-cell profiling of patient samples for severe conditions such as RIME.
Our source code, utility scripts and links to processed data and results are all available on our lab's GitHub: lnkd.in/g7EdGYuu
Hope you enjoy reading it and reach out if you have any questions or feedback!
Big thanks to Cell Reports Methods and their editorial team for the efficient review
Our results highlight the importance of distance stratification in capturing differences in long-range loops, differences in sensitivity across different statistical models and provides overall best practices for differential HiChIP analysis.
good collaborator Katia Georgopoulos in annotation of the results, we implemented a unified framework with all different approaches to date, developed performance metrics and systematically evaluated tools/tests utilized by us and others on multiple different HiChIP datasets.
We and others have worked on this problem but realized the variability in effectiveness of different approaches across different data sets. In this work, led by Sourya Bhattacharyya (now at Empirico) and Daniela Salgado Figueroa (UCSD Bioinformatics PhD student) in my lab and with help from our
Our latest paper on comparative analysis of HiChIP data is now online! HiChIP is one of the most useful/practical assays to profile 3D genome organization and chromatin loops but has its challenges in the data analysis especially when it comes to comparative analysis.
Important well-explained summary: “NIH has awarded nearly 3,000 fewer research project grants than it did the previous year”.
I have
NIGMS R35, impact score 12
NIHGRI R21, 4th percentile
NHGRI R01, 7th percentile (co-I)
and it seems like none will be funded. 0/3.
PO (who has been very helpful) said "Unfortunately, I do not expect this application will be selected for funding in FY25."
😭
Oh my god 😱😱 good luck Anders. These are amazing scores..We have multiple single digit %ile grants with collaborators.. one is a resubmission after multiple submissions finally making “the cut” just to have the goal post moved 😥 fingers crossed for some last minute miracle for all of us
Funding policy for 2025 from NCI. Was just released: 4 percentile…maybe!
www.cancer.gov/grants-train...