Nature Computational Science wants to publish your computational social science research.

Nonlinear optical computations have been essential yet challenging for developing optical neural networks with appreciable expressivity. In this paper, light scattering is combined with optical nonlinearity to empower a high-performance, large-scale nonlinear photonic neural system.

While large-scale GPS location datasets have been instrumental to applications in epidemiology, there are still several challenges with these data that should be considered and addressed to make data-driven epidemiology more reliable.

The parallels between natural language and antibody sequences could serve as a stepping stone to using deep language models for analyzing antibody sequences. This Perspective discusses how issues in antibody language model rule mining could be addressed by linguistically formalizing the antibody language.

The downselection of compounds for synthesis is a key challenge in molecular design cycles that typically relies on expert chemist intuition. Fromer and Coley propose a cost-aware method to automatically select compounds and synthetic routes.

Nonlinear optical computations have been essential yet challenging for developing optical neural networks with appreciable expressivity. In this paper, light scattering is combined with optical nonlinearity to empower a high-performance, large-scale nonlinear photonic neural system.

Seqwalk is a scalable method for designing orthogonal DNA barcode libraries, producing one million barcodes in 20 s on a standard laptop.

A self-consistent iterative procedure is proposed to compute the committor function for rare events, via a variational principle, and extensively sample the transition state ensemble, allowing for the identification of the relevant variables in the process.

This paper introduces an algorithm to uncover laws of skill acquisition from naturally occurring data. By combining deep learning and symbolic regression, it accurately identifies cognitive states and extracts algebraic equations.

The authors develop the tool RESHAPE to share reference panels in a safer way. The genome–phenome links in reference panels can generate re-identification threats and RESHAPE breaks these links by shuffling haplotypes while preserving imputation accuracy.

Human mobility research intersects with various disciplines, with profound implications for urban planning, transportation engineering, public health, disaster management, and economic analysis. Here, we discuss the urgent need for open and standardized datasets in the field, including current challenges and lessons from other computational science domains, and propose collaborative efforts to enhance the validity and reproducibility of human mobility research.

Software is much more than just code. It is time to confront the complexity of licenses, uses, governance, infrastructure and other facets of software in science. Their influence is ubiquitous yet overlooked.

Nature Computational Science wants to publish your computational social science research.

As machine learning models are becoming mainstream tools for molecular and materials research, there is an urgent need to improve the nature, quality, and accessibility of atomistic data. In turn, there are opportunities for a new generation of generally applicable datasets and distillable models.