Our paper is now online at Sci Adv: https://t.co/1790lwk9Kh See also the accompanying news: https://t.co/H3EZghJt1V

Hmm, I assume these posts were made by AI? Anyway, very impressive summary of our latest preprint.

Check out our recent manuscript that studies the interactions between small molecules and biomolecular condensates with all-atom simulations:

Our findings shed light on the significant regulatory roles of bio condensate and DNA linker length and help bridge the gap between in vivo and in vitro observations.

Nucleosome condensate and linker DNA alter chromatin folding pathways and rates [Qiu et al, 2024] https://t.co/2MYkfyk67M ▶️residue-level coarse-grained models; non-Markovian dynamics ▶️10n bp DNA linker lengths favor zigzag fibrils ▶️10n+5 bp chromatin loses unique conformations

Scaling Graph Neural Networks to Large Proteins 1. This paper introduces the DISPEF dataset, specifically designed for benchmarking graph neural networks (GNNs) on large, biologically relevant proteins. DISPEF contains over 200,000 proteins with implicit solvation free energies,

I am excited to share our latest #preprint: ChromoGen: Diffusion model predicts single-cell chromatin conformations https://t.co/h5FORbb0io As the title suggests, we achieved de novo prediction of 3D chromatin structures using DNA sequence and ATAC-seq using AI.

Our explicit ion paper is now online at Elife: https://t.co/4AlISHvEIL. But who has time to read anyway? Luckily, @XingchengLin made an excellent video that you can watch at:

Our review on chromatin organization is online at the Annual Review of Biophysics! Spoiler alert, we took a more physical chemist's perspective on the problem. https://t.co/5g7m9CoXOk

Thanks to the efforts of our group members. This new work provides a new role of micropolarity in condensates.

You can also listen to an audio summary here:

Interested in IDPs and biomolecular condensates? Do you ever wonder why IDPs adopt low-complexity domains? How do you map a given protein sequence into stickers and spacers? We attempt to address these questions in our latest preprint.

A fruitful collaboration with Bin Zhang @binzmit reveals the nanometer scale interfacial environment of phase separated condensates. In @eLife: Frustrated Microphase Separation Produces Interfacial Environment within Biological Condensates

We welcome new postdoc, Joe Paggi, and grad students Camryn Carter and Ivan Riveros to the group. I am very much looking forward to working with you all.

Our paper just appeared online at ACS Cen Sci! Really impressed with the journal's efficiency.

I am excited to share our whole nucleus study that provides structural and dynamic modeling of the diploid genome (100kb resolution), lamina, speckles, and nucleoli. We have consolidated our modeling effort into an open-source GPU-enabled software.

Our OpenABC paper just appeared online: https://t.co/i2Or11vfov During revision, we also added multiple new force fields to the software, including the wonderful Mpipi for RNA from @rcollepardo

I am very excited to share our latest preprint on building transferable CG force fields with GNNs and contrastive learning. We believe the two techniques offer a path to build CG models that rival the accuracy of atomistic models.

Myself and Anand @mbuanand are looking forward to Bin Zhang @binzmit as our next speaker in the Integrative modelling seminar series. Bin will share his research on IDP and Genome biophysics. Save the date (13 September at 5.30 pm IST ) and DM us for meeting link.

Our paper on efficiently inverting Hi-C contacts to interaction energies is out: https://t.co/XPSNmQQE7W. This inversion could facilitate polymer simulations as well as contact feature extraction. Great job, Greg!