Research articles

Leveraging both the simple pileup input and full-alignment input, small variant calling using noisy long reads has improved speed and accuracy.

The vulnerability of quantum machine learning models against adversarial noises, together with a defense strategy way out of this dilemma, is demonstrated experimentally with a programmable superconducting quantum processor.

A computational method is introduced for mutational intratumor heterogeneity inference from noisy genotype matrices derived from single-cell sequencing data. The proposed method is shown to be accurate and faster than available alternatives.

A systematic framework is introduced to calculate the effective carrier lifetime in semiconductor crystals under realistic conditions that are comparable with experiments. It helps explain the discrepancy between the calculated and experimental lifetimes in hybrid perovskites.

Accurate structural brain connectivity estimation is key to uncovering brain–behavior relationships. ReAl-LiFE, a GPU-accelerated approach, is applied for fast and reliable evaluation of individualized brain connectomes at scale.

A dynamic probabilistic algorithm that integrates many variables over time for forecasting severe acute graft-versus-host disease is proposed to improve healthcare decisions for individual patients on a case-by-case basis.

Scallop2 enables a more accurate assembly of transcripts at both single-cell resolution and sample level through a suite of algorithms that leverage the multi-end and paired-end information in Smart-seq3 and Illumina RNA-seq data.

mm2-fast is an accelerated version of minimap2, a popular software for long-read data analysis. mm2-fast introduces high-performance parallel computing techniques to reduce the overall runtime of minimap2.

Networks offer a powerful visual representation of complex systems. This study introduces network visualizations that are easy to interpret and can help explore large datasets, such as the map of all molecular interactions in the cell.