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The identification of new drug targets is highly challenging, particularly for diseases of the brain. This study describes a general computational gene regulatory framework called CRAFT for drug target discovery, and the authors use CRAFT to identify the microglial membrane receptor Csf1R as a potential therapeutic target for epilepsy.

The flagship paper of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium describes the generation of the integrative analyses of 2,658 cancer whole genomes and their matching normal tissues across 38 tumour types, the structures for international data sharing and standardized analyses, and the main scientific findings from across the consortium studies.

Analyses of 2,658 whole genomes across 38 types of cancer identify the contribution of non-coding point mutations and structural variants to driving cancer.

In this study the authors consider the structural variants (SVs) present within cancer cases of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium. They report hundreds of genes, including known cancer-associated genes for which the nearby presence of a SV breakpoint is associated with altered expression.

This Perspective from Summerfield et al. considers the impacts of advanced artificial intelligence systems on the process and function of democracy. The authors explore a wide range of potential risks and opportunities.

Integrative analyses of transcriptome and whole-genome sequencing data for 1,188 tumours across 27 types of cancer are used to provide a comprehensive catalogue of RNA-level alterations in cancer.

With the generation of large pan-cancer whole-exome and whole-genome sequencing projects, a question remains about how comparable these datasets are. Here, using The Cancer Genome Atlas samples analysed as part of the Pan-Cancer Analysis of Whole Genomes project, the authors explore the concordance of mutations called by whole exome sequencing and whole genome sequencing techniques.

The characterization of 4,645 whole-genome and 19,184 exome sequences, covering most types of cancer, identifies 81 single-base substitution, doublet-base substitution and small-insertion-and-deletion mutational signatures, providing a systematic overview of the mutational processes that contribute to cancer development.

Understanding deregulation of biological pathways in cancer can provide insight into disease etiology and potential therapies. Here, as part of the PanCancer Analysis of Whole Genomes (PCAWG) consortium, the authors present pathway and network analysis of 2583 whole cancer genomes from 27 tumour types.

There’s an emerging body of evidence to show how biological sex impacts cancer incidence, treatment and underlying biology. Here, using a large pan-cancer dataset, the authors further highlight how sex differences shape the cancer genome.

In somatic cells the mechanisms maintaining the chromosome ends are normally inactivated; however, cancer cells can re-activate these pathways to support continuous growth. Here, the authors characterize the telomeric landscapes across tumour types and identify genomic alterations associated with different telomere maintenance mechanisms.

Whole-genome sequencing data from more than 2,500 cancers of 38 tumour types reveal 16 signatures that can be used to classify somatic structural variants, highlighting the diversity of genomic rearrangements in cancer.

Viral pathogen load in cancer genomes is estimated through analysis of sequencing data from 2,656 tumors across 35 cancer types using multiple pathogen-detection pipelines, identifying viruses in 382 genomic and 68 transcriptome datasets.

Analysis of cancer genome sequencing data has enabled the discovery of driver mutations. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium the authors present DriverPower, a software package that identifies coding and non-coding driver mutations within cancer whole genomes via consideration of mutational burden and functional impact evidence.

A pan-cancer genomic analysis reports the effects of structural variations on chromatin domains (TADs). Most TAD disruptions do not result in appreciable changes in expression of nearby genes.

An analysis of 2,954 genomes from 38 cancer subtypes identified 19,166 retrotransposition events in 35% of samples. Aberrant LINE-1 retrotranspositions can lead to the deletion of tumor-suppressor genes as well as the amplification of oncogenes.

Whole-genome sequencing data for 2,778 cancer samples from 2,658 unique donors across 38 cancer types is used to reconstruct the evolutionary history of cancer, revealing that driver mutations can precede diagnosis by several years to decades.

Some cancer patients first present with metastases where the location of the primary is unidentified; these are difficult to treat. In this study, using machine learning, the authors develop a method to determine the tissue of origin of a cancer based on whole sequencing data.

The authors present SVclone, a computational method for inferring the cancer cell fraction of structural variants from whole-genome sequencing data.

Many tumours exhibit hypoxia (low oxygen) and hypoxic tumours often respond poorly to therapy. Here, the authors quantify hypoxia in 1188 tumours from 27 cancer types, showing elevated hypoxia links to increased mutational load, directing evolutionary trajectories.

Multi-omics datasets pose major challenges to data interpretation and hypothesis generation owing to their high-dimensional molecular profiles. Here, the authors develop ActivePathways method, which uses data fusion techniques for integrative pathway analysis of multi-omics data and candidate gene discovery.

Cancers evolve as they progress under differing selective pressures. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, the authors present the method TrackSig the estimates evolutionary trajectories of somatic mutational processes from single bulk tumour data.

A flexible AI framework integrates multimodal neurology work-up data to estimate amyloid and tau burden, supporting scalable biomarker stratification for Alzheimer’s disease research and trial screening.

Papers should be published according to the merit of their scientific contribution, not the polish of their presentation, says Michael White.

Sepsis may promptly develop into lethal organ failure, so early diagnosis and treatment planning are essential. Here the authors use machine learning to develop a six-gene signature, termed Sepset, for initial diagnosis, and integrate Sepset into a microfluidic-based bench-side platform for predicting the prognosis of suspected sepsis suitable for the clinic.

Efficient, large-scale genomic analysis is facilitated on the cloud by a computational tool with error-diagnosing and self-healing capabilities.

GIANT, a genetically informed brain atlas, integrates genetic heritability with neuroanatomy. It shows strong neuroanatomical validity and surpasses traditional atlases in discovery power for brain imaging genomics.

Analysis of whole-genome sequencing data across 2,658 tumors spanning 38 cancer types shows that chromothripsis is pervasive, with a frequency of more than 50% in several cancer types, contributing to oncogene amplification, gene inactivation and cancer genome evolution.

Analysis of mitochondrial genomes (mtDNA) by using whole-genome sequencing data from 2,658 cancer samples across 38 cancer types identifies hypermutated mtDNA cases, frequent somatic nuclear transfer of mtDNA and high variability of mtDNA copy number in many cancers.

Stone skipping on water is a very classical phenomenon, but the relevant fluid dynamics is more complicated than what is normally expected. Here, Belden et al. study the effect of elasticity on the skipping dynamics and show why soft spheres can skip much easier than solid spheres.

Two programs, GRAPE and GARLIC, work together to first predict biosynthetic gene clusters responsible for the production of polyketides and nonribosomal peptides, then link sequenced gene clusters to known and unknown natural products.

As page composition from digitised information replaces the manual assembly of type, the printing industry struggles to absorb a technology in which the compositor becomes a computer operator and the production controller a systems analyst.

Meta-analysis of genome-wide association studies on Alzheimer’s disease and related dementias identifies new loci and enables generation of a new genetic risk score associated with the risk of future Alzheimer’s disease and dementia.

Knitted fabrics are prized for their stretchability, breathability, and long-wearability in everyday life. This study combines experiments and simulations to present a micromechanical approach to understanding the origin of the anisotropic elasticity of four canonical patterns of knitted fabrics.

Sjögren’s syndrome, a disease that primarily affects women, is poorly understood. Here, the authors combine data from a large cohort of patients and healthy controls to identify biomarkers that distinguish patient subgroups to improve our understanding of the disease and facilitate drug development.

Saturn satellite slides smoothly into position.

Television show hopes to convince participants they are in orbit.