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Lossless data compression by large models

Effective lossless compression requires that frequent patterns in the data can be identified. Li et al. explore using deep learning models to more effectively compress text, audio and video data.

Ziguang Li
Chao Huang
Ming Li
Research01 May 2025
Nature Machine Intelligence

Volume: 7, P: 794-799
Accurate and robust protein sequence design with CarbonDesign

Deep learning has led to great advances in predicting protein structure from sequences. Ren and colleagues present here a method for the inverse problem of finding a sequence that results in a desired protein structure, which is inspired by various components of AlphaFold combined with Markov random fields to decode sequences more efficiently.

Milong Ren
Chungong Yu
Haicang Zhang
Research23 May 2024
Nature Machine Intelligence

Volume: 6, P: 536-547
CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction

Protein structure prediction is a challenge. A new deep learning framework, CopulaNet, is a major step forward toward end-to-end prediction of inter-residue distances and protein tertiary structures with improved accuracy and efficiency.

Fusong Ju
Jianwei Zhu
Dongbo Bu
ResearchOpen Access05 May 2021
Nature Communications

Volume: 12, P: 1-9
Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials

Presenting KnotFold, an application for accurately predicting RNA secondary structures, including pseudoknots.

Tiansu Gong
Fusong Ju
Dongbo Bu
ResearchOpen Access09 Mar 2024
Communications Biology

Volume: 7, P: 1-13
Insights into the transmission of respiratory infectious diseases through empirical human contact networks

Chunlin Huang
Xingwu Liu
Dongbo Bu
ResearchOpen Access16 Aug 2016
Scientific Reports

Volume: 6, P: 1-11

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Lossless data compression by large models

Accurate and robust protein sequence design with CarbonDesign

CopulaNet: Learning residue co-evolution directly from multiple sequence alignment for protein structure prediction

Accurate prediction of RNA secondary structure including pseudoknots through solving minimum-cost flow with learned potentials

Insights into the transmission of respiratory infectious diseases through empirical human contact networks

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