Browse our Tools and Resources

An inference paradigm for extracting neuronal correlations from two-photon imaging data, without requiring intermediate spike deconvolution, provides significant performance gains over existing methods as demonstrated by theoretical analysis, simulation studies, and real-data applications.

One hundred one high-quality drosophilid genomes are released, along with low-cost assembly workflows, as an open community resource for studying genetics, ecology, and evolution in this important model system.

The World Mortality Dataset and paper is the largest dataset of all-cause mortality currently in existence for tracking mortality and excess mortality during the COVID-19 pandemic.

NICEdrug.ch is a resource allowing systematic and large-scale computational analysis of drug biochemistry, enzymatic targets, and toxicity in the context of cellular metabolism.

A novel deep-learning framework shows how to interpret and decode raw neural recordings, avoiding the need for strong prior hypotheses, revealing a novel representation of head direction.

Fast and flexible estimation of effective migration surfaces (FEEMS) is a new statistical method that can quickly infer and visualize patterns of migration from genetic data with spatial coordinates.

A newly developed lateral flow assay can diagnose mutational signatures of major SARS CoV-2 variants in a rapid, inexpensive, and sequence-free manner.

Epidemiological and viral sequence data can be combined to provide standardised feedback on cases of hospital onset COVID-19 infection that would be useful for infection prevention and control.

PCR testing for SARS-CoV-2 from samples taken from smartphone screens, Phone Screen Testing, provides a sensitive, cost-effective, simple, and non-invasive new method that could boost COVID-19 mass test screening.

Single-cell mRNA sequencing on hemocytes of penaeid shrimp revealed six types of hemocytes, type markers, differentiation pathways, and different immune roles among these subpopulations based on their transcriptional profiles.