I’m excited to announce that our paper on viral molecular mimicry just came out! Molecular mimicry occurs when pathogens “mimic” host protein structure. Here, we explore mimicry across the human virome and its connection to autoimmunity. @MelamedEsthernature.com/articles/s41467-0…
Excited to share our latest #IMPACC study on patient subtype discovery using longitudinal multi-omics! We identified 5 subtypes among 1,000 hospitalized #COVID19 patients, highlighting the link between distinct immune responses in those with similar respiratory status to various acute complications and #LongCOVID risk. biorxiv.org/content/10.1101/…
This work is co-led by wonderful students Kexin, Yutong, @colemag9, collaborators @VirusesImmunity, @JoannDArce, Lauren, and the #IMPACC consortium team.
We are excited to announce that the 3rd (Public) CMI-PB Challenge is officially underway! Test out your modeling skills to predict immune responses to B. pertussis #whoopingcough booster vaccination using multi-omics datasets for a chance to win. #bioinformatics#immunology (1/5)
I'm thrilled to share our new #Bioconductor package, nipalsMCIA, which performs multi-omic dimensionality reduction using the NIPALS algorithm. It is fast (especially for large datasets), and user friendly. Give it a try!
biorxiv.org/content/10.1101/… (1/4)
Congratulations to our #IMPACC team members @LeyingGuan@JeremyGygi@colemag9@sciRPatel for our newly published COVID-19 multiomics paper in JCI! Grateful to be working with all of you for the past few years!
A new study led by #CZBiohubSF & @UCSF researchers provides fresh insights into why age is a major risk factor for severe #COVID. It is the most comprehensive analysis to date of how age affects the immune response to #SARSCoV2. 1/7
Read in @ScienceTM ⤵️
bit.ly/4aUR2Mc
So happy to have had the chance to present our work on SPEAR with @LeyingGuan and @skleinstein at the @hipcProject annual meeting! Grateful for all the valuable insight and interest.
On both the TCGA and COVID-19 datasets, we demonstrate that SPEAR is able to construct biologically significant multi-omic factors, finding key pathways and insights that are backed by literature.
(12/13)
If you are working with any type of “omics” data and have a desire to find predictive analytes for a response of interest, we offer SPEAR as a free publicly available R-package. Feel free to reach out with any questions you may have.
biorxiv.org/content/10.1101/…
Thank you!
(13/13)