sequence-to-function modeling

Massively parallel quantification and prediction of monomeric protein yield in Escherichia coli

The paper develops a scalable assay and a protein language model to predict monomeric yield of proteins in E. coli, showing it can be learned and designed.

De novo design of mini-proteins as specific binders to PACAP-38, a key mediator of migraine

This study designs mini-proteins that bind PACAP-38 with high affinity, showing improved potency and stability compared to earlier versions.

GLOM TGITO: multiscale protein modelling and multiview landscape-guided sequence discovery

The paper introduces GLOM-TGITO, a method for protein design that combines multiscale modeling with multiview landscape-guided optimization, achieving high accuracy and novel sequence discovery.

PepPr: De Novo peptide sequencing with peptide priors

PepPr improves peptide sequencing by integrating peptide priors, enhancing reference and variant peptide identification while maintaining discovery flexibility.

Sequence design for three-dimensional genome folding using Akita Semifreddo

This paper introduces Akita Semifreddo, a framework for designing DNA sequences that produce specific 3D genome folding patterns, demonstrating the ability to create boundaries, dots, and flames with controlled strengths.

RiboCouple links RNA backbone generation to sequence design through a learned interaction topology

The paper introduces RiboCouple, a method that links RNA backbone geometry to sequence design using learned interaction topologies, improving refolding validity in RNA structure prediction.

Sequence-dependent conformational and mechanical landscapes of double-stranded nucleic acids

This study introduces cgNA+, a model predicting sequence-dependent mechanical properties of dsNAs with high accuracy, revealing hidden regulatory layers in nucleic acid mechanics.

Human-specific CCG-repeat insertion in the RBFOX1 promoter implicated in autism and speech enhances EGR1-responsive activity

A human-specific CCG insertion in the RBFOX1 promoter boosts EGR1-driven reporter activity in HEK293T cells, as does an autism-linked CCG-gaining duplication in PTCHD1.

Accessing Enzyme Kinetic Data and Prediction Methods at Scale

OpenKinetics Predictor unifies thirteen enzyme kinetic predictors behind one interface and API; on E. coli iML1515, eight kcat predictors correlate pairwise at r 0.08 to 0.67.

Pruning the Search, Not the Signal: Adaptive-Banding Needleman-Wunsch Sequence Alignment via Protein Language Model Confidence

This paper introduces AB-NW, an adaptive-banding Needleman-Wunsch alignment method that improves speed while maintaining accuracy on challenging sequence alignment tasks.

De novo design of small cyclic peptide inhibitors from non-canonical amino acids by cofolding-guided search

This paper introduces nCycle-Forge, a computational method for designing cyclic peptides that outperforms existing approaches in hit rate and potency against two targets.

Lossless compression of protein databases for efficient and accurate metagenomic sequence classification with Centrifuger

The paper introduces a lossless compression algorithm for protein databases, improving memory efficiency and classification accuracy in Centrifuger for metagenomic analysis.

Optimized Multiple Circular Sequence Alignment for Cyclic Peptide Motif Discovery

The paper optimizes multiple circular sequence alignment for cyclic peptides, achieving faster performance while maintaining alignment quality.

A Unified 3D Generative Model for Synthesizable Structure-Based Drug Design

This paper introduces LDDM, a generative model for drug design that produces synthetically accessible compounds validated experimentally for five protein targets.

Functional alignment of protein language models via reinforcement learning

This paper introduces RLXF, a framework that aligns protein language models with experimental functional goals, improving the generation of high-functioning protein variants.

Coverage Geometry and Heuristic Discovery Times in Protein Sequence Space

The paper introduces a geometric framework to analyze protein sequence space coverage and connects it to heuristic discovery times using a stochastic exploration model.

Sequence-free landscape inference for directed evolution

This paper introduces SLIDE, a method to estimate landscape ruggedness in directed evolution using population-level phenotypic data and mutation rate, improving selection strategies for protein design.

Gradient-based Optimization for mRNA Sequence Design

The paper introduces ID3, a framework for optimizing mRNA sequences using gradient-based methods, balancing multiple properties while preserving amino acid sequences.

Dynamic Hierarchical Interleaved Bloom Filter: An Updatable Index for Large-Scale Fast Sequence Search

This paper introduces a dynamic and updatable sequence-search index called Dynamic HIBF, which efficiently handles large-scale data updates and outperforms existing methods in speed.

A multi-tissue epigenomic atlas links the sheep non-coding genome to domestication and complex traits

SheepEpimap combines 516 histone CUT&Tag, ATAC-seq and RNA-seq datasets from 43 sheep tissues to annotate 2.93 million cis-regulatory elements and 145,407 allele-specific variants for trait interpretation.

A membrane insertion code for intrinsically disordered proteins

The paper identifies sequence determinants for aromatic residue insertion into membranes and develops a predictor model with high accuracy.

Trust-Aware Sequence-to-Function Modelling in Regulatory Genomics

The paper introduces RegTrust-XAI, a trust-aware framework for sequence-to-function models in regulatory genomics, showing how reliability, explanation validity, and sequence novelty are distinct properties.

Improved inference of multiscale sequence statistics in generative protein models

This paper introduces a new regularization strategy for generative protein models that improves the inference of multiscale sequence statistics, enabling the generation of functional and diverse protein sequences.

Functional pocketomes and complete allosteric maps of five protein kinases

Energy-model maps of five human kinases show conserved distance-dependent decay of inhibitory allostery, but distal allosteric pockets and activating sites diverge between kinases.

Fast remote nucleotide sequence alignment with Riboseek

Riboseek is a fast and sensitive sequence alignment tool for RNA and DNA that uses di-mers for alignment, outperforming BLASTN and nhmmer in speed and sensitivity.

Theseus: Fast and Optimal Affine-Gap Sequence-to-Graph Alignment

Theseus provides a fast and optimal affine-gap sequence-to-graph alignment algorithm, outperforming existing methods in speed while maintaining optimality.

AINN-Express: A Leakage-Aware, Sequence-Only Predictor of VHH Antibody Expression Built on the AINN-P1 Protein Foundation Model

AINN-Express predicts VHH antibody expression using only sequence data, achieving high ROC-AUC scores in both known and new programs without requiring structural data or task-specific training.

pHaseMD4AI: Phase-Space Dynamics Dataset with Chemical and pH Perturbations for Physically and Kinetically Consistent Biomolecular AI

The paper introduces pHaseMD4AI, a molecular dynamics dataset with chemical and pH perturbations, to support biomolecular AI research and benchmarking.

Beyond the Static Caliper: Dynamical Translocases and the Mathematical Imperative for Single-Molecule Proteomics

This paper proposes dynamical translocases and Physics-Informed Machine Learning to overcome biophysical limitations in single-molecule proteomics, achieving >90% accurate amino acid classification.

Context-aware sequence-to-function model of human gene regulation

The paper introduces Corgi, a context-aware sequence-to-function model that predicts gene expression and epigenetic signals across unseen cell types using DNA sequence and trans-regulator expression.