iiinova — where your digital self keeps evolving

Leo Zang @leozang.bsky.social · 05/03/2025

Computational protein design - "This Primer provides an introduction to the main approaches in computational protein design, covering both physics-based and machine-learning-based tools. It aims to be accessible to biological, physical and computer scientists alike." www.nature.com/articles/s43...

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Leo Zang @leozang.bsky.social · 30/01/2025

Protein-Based Degraders: From Chemical Biology Tools to Neo-Therapeutics - "we provide a comprehensive and critical review of studies that have used proteins and peptides to mediate the degradation and hence the functional control of otherwise challenging disease-relevant protein targets.

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Leo Zang @leozang.bsky.social · 23/01/2025

Inference-Time Alignment in Diffusion Models with Reward-Guided Generation: Tutorial and Review arxiv.org/abs/2501.09685

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Leo Zang @leozang.bsky.social · 18/01/2025

Targeting protein–ligand neosurfaces with a generalizable deep learning tool | @Nature - MaSIF-neosurf can design binders for protein-ligand complexes, targeting neosurfaces (i.e., ligand-induced structural changes on the protein surface) Link: www.nature.com/articles/s41...

nature.com

Targeting protein–ligand neosurfaces with a generalizable deep learning tool - Nature

A computational deep learning approach is used to design synthetic proteins that target the neosurfaces formed by protein–ligand interactions, with applications in the development of new therapeutic m...

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Leo Zang @leozang.bsky.social · 17/01/2025

Massively parallel characterization of transcriptional regulatory elements - Develope an optimized lentiMPRA (lentiviral massively parallel reporter assay) method to test regulatory activity of >680,000 sequences across three cell types (HepG2, K562, WTC11) Link: www.nature.com/articles/s41...

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Leo Zang @leozang.bsky.social · 09/01/2025

DNALONGBENCH: A Benchmark Suite for Long-Range DNA Prediction Tasks www.biorxiv.org/content/10.1... Engineering of CRISPR-Cas PAM recognition using deep learning of vast evolutionary data www.biorxiv.org/content/10.1...

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Leo Zang @leozang.bsky.social · 27/12/2024

A review of deep learning models for the prediction of chromatin interactions with DNA and epigenomic profiles | @BriefingBioinfo Link: academic.oup.com/bib/article/...

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Leo Zang @leozang.bsky.social · 19/12/2024

Leveraging ancestral sequence reconstruction for protein representation learning www.nature.com/articles/s42... Guiding Generative Protein Language Models with Reinforcement Learning arxiv.org/abs/2412.12979

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Leo Zang @leozang.bsky.social · 16/12/2024

Harnessing the biology of regulatory T cells to treat disease - "This Review will discuss recent advances in our understanding of human Treg cell biology, with a focus on mechanisms of action and strategies to assess outcomes of Treg cell-targeted therapies." www.nature.com/articles/s41...

nature.com

Harnessing the biology of regulatory T cells to treat disease - Nature Reviews Drug Discovery

Regulatory T cells keep the immune system in check to maintain homeostasis and restrain inflammation. This Review discusses strategies to harness these cells therapeutically for autoimmunity, transpla...

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Leo Zang @leozang.bsky.social · 16/12/2024

Annotation-guided Protein Design with Multi-Level Domain Alignment arxiv.org/abs/2404.16866 BEACON: Benchmark for Comprehensive RNA Tasks and Language Models arxiv.org/abs/2406.10391

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Leo Zang @leozang.bsky.social · 15/12/2024

mRNA m6A detection | @MethodsPrimers - "This Primer outlines the available tools for detecting and mapping m6A, discusses the strengths and limitations of each method and offers guidance on selecting the most suitable approach." www.nature.com/articles/s43...

nature.com

mRNA m6A detection - Nature Reviews Methods Primers

N6-methyladenosine (m6A) is an mRNA modification influencing gene expression. Advanced methodologies for mapping m6A enhance understanding of its dynamic roles and interactions. In this Primer, Moshit...

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Leo Zang @leozang.bsky.social · 14/12/2024

Concept Bottleneck Language Models For protein design - Introduce CB-pLM (Concept Bottleneck Protein Language Models) from 24M to 3B, trained on UniRef50 and SwissProt over 718 concepts (including Cluster name, Biological process, and Biopython-derived features, etc.) arxiv.org/abs/2411.06090

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Leo Zang @leozang.bsky.social · 12/12/2024

Benchmarking recent computational tools for DNA-binding protein identification - "we conduct an unbiased benchmarking of 11 state-of-the-art computational tools as well as traditional tools such as ScanProsite, BLAST, and HMMER for identifying DBPs." Link: academic.oup.com/bib/article/...

academic.oup.com

Benchmarking recent computational tools for DNA-binding protein identification

Abstract. Identification of DNA-binding proteins (DBPs) is a crucial task in genome annotation, as it aids in understanding gene regulation, DNA replicatio

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Leo Zang @leozang.bsky.social · 27/11/2024

Comprehensive prediction and analysis of human protein essentiality based on a pretrained large language model | @NatComputSci - PIC (Protein Importance Calculator), an ESM2-based deep learning model, predicts protein essentiality across three biological levels Link: www.nature.com/articles/s43...

nature.com

Comprehensive prediction and analysis of human protein essentiality based on a pretrained large language model - Nature Computational Science

This study introduces the Protein Importance Calculator (PIC), a deep learning model designed to predict human essential proteins (HEPs) crucial for survival and development. Unlike conventional metho...

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Leo Zang @leozang.bsky.social · 27/11/2024

Using artificial intelligence to document the hidden RNA virosphere - PRIME, protein language model (same as ESM-2 650M architecture) pretrained on 96 million sequences with optimal growth temperatures (OGTs annotated by [1]) with MLM, MSE, and Correlation Loss Link: www.science.org/doi/10.1126/...

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Leo Zang @leozang.bsky.social · 27/11/2024

Getting aligned on representational alignment - "In this Perspective, we survey the exciting recent developments in representational alignment research in the fields of cognitive science, neuroscience, and machine learning" Link: arxiv.org/abs/2310.13018

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Leo Zang @leozang.bsky.social · 25/11/2024

More: - BindingDB in 2024: a FAIR knowledgebase of protein-small molecule binding data academic.oup.com/nar/advance-... - BFVD—a large repository of predicted viral protein structures academic.oup.com/nar/advance-...

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Reposted by Leo Zang

Martin Steinegger 🇺🇦 @martinsteinegger.bsky.social · 23/11/2024

Our Big Fantastic Virus Database (BFVD) is now published NAR! It contains protein structure predictions of major viral clades, enhanced by petabase-scale homology search and it's explorable on the web. 🌐 bfvd.foldseek.com 💾 bfvd.steineggerlab.workers.dev 📄 academic.oup.com/nar/advance-...

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Leo Zang @leozang.bsky.social · 21/11/2024

Discovery and significance of protein-protein interactions in health and disease | @cellpressnews.bsky.social Review Link: www.cell.com/cell/fulltex...

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Leo Zang @leozang.bsky.social · 21/11/2024

Database updates -The Pfam protein families database: embracing AI/ML academic.oup.com/nar/advance-... - UniProt: the Universal Protein Knowledgebase in 2025 academic.oup.com/nar/advance-... - RASP v2.0: an updated atlas for RNA structure probing data academic.oup.com/nar/advance-...

academic.oup.com

UniProt: the Universal Protein Knowledgebase in 2025

Abstract. The aim of the UniProt Knowledgebase (UniProtKB; https://www.uniprot.org/) is to provide users with a comprehensive, high-quality and freely acce

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Leo Zang @leozang.bsky.social · 19/11/2024

InterPLM: Discovering Interpretable Features in Protein Language Models via Sparse Autoencoders www.biorxiv.org/content/10.1... - Use sparse autoencoders (SAEs) to extract and analyze interpretable features from ESM-2-8M

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Leo Zang @leozang.bsky.social · 16/11/2024

miRBench: A Comprehensive microRNA Binding Site Prediction Training and Benchmarking Dataset Preprint: www.biorxiv.org/content/10.1... GitHub: github.com/katarinagres...

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Leo Zang @leozang.bsky.social · 16/11/2024

AlphaBind, a Domain-Specific Model to Predict and Optimize Antibody-Antigen Binding Affinity - Encode antibody and antigen with ESM2-nv (ESM2 but on NVIDIA), concatenate embeddings and feed into a lightweight transformer (4 attention heads, 7 layers) to predict binding affinity

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Leo Zang @leozang.bsky.social · 16/11/2024

The word limit here makes it difficult to post a summary thread 🤔

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Leo Zang @leozang.bsky.social · 14/11/2024

Collection of Papers and Posts www.leozang.com/Paper-Collec...

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