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This work introduces HANNA, a strictly consistent machine learning model for predicting phase equilibria and other thermodynamic properties of multi-component mixtures only from the molecular structure.

Robustness checks and reproduction of analyses with existing and updated data based on 110 articles in economics and political science journals with data and code-sharing requirements found high levels of robustness and reproducibility and determined that robustness was not dependent on author characteristics or data availability.

Here the authors compare genetic testing strategies in rare movement disorders, improve diagnostic yield with genome analysis, and establish CD99L2 as an X-linked spastic ataxia gene, showing that CD99L2–CAPN1 signaling disruption likely drives neurodegeneration.

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.

Elevated serum levels of phosphorylated tau are not specific to Alzheimer’s disease and may also serve as a diagnostic tool for the most common types of systemic amyloidosis, with potential utility in distinguishing amyloidosis-related polyneuropathy from polyneuropathy of other etiologies.

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.

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.

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.

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.

Genome-wide analyses identify 30 independent loci associated with obsessive–compulsive disorder, highlighting genetic overlap with other psychiatric disorders and implicating putative effector genes and cell types contributing to its etiology.

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.

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.

Genomic analyses applied to 14 childhood- and adult-onset psychiatric disorders identifies five underlying genomic factors that explain the majority of the genetic variance of the individual disorders.

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.

Ferrimagnets possess multiple spin sub-lattices resulting in a complex magnon band structure and subtle spin transport across interfaces. Here, the authors show how the spin Seebeck effect, the thermal generation of pure spin current, may be an effective tool to study these magnetic excitations.

Glaciers lost 408 ± 132 Gt of mass during the hydrological year 2025, equivalent to 1.1 ± 0.4 mm sea-level rise. Since 1975, glacier mass loss has totalled 9,583 ± 1,211 Gt, equivalent to 26.4 ± 3.3 mm of sea-level rise, with six of the highest mass-loss years on record occurring in the past seven years.

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.

Endogenous retroviruses, or genomic relics of ancient viral infection, have been associated with certain neurodegenerative diseases. Here, Liu et al. report a pathway by which reactivated viral gene products contribute to intercellular protein aggregate spreading.

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.

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.

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.

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.

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.

A genome-wide association study including over 76,000 individuals with schizophrenia and over 243,000 control individuals identifies common variant associations at 287 genomic loci, and further fine-mapping analyses highlight the importance of genes involved in synaptic processes.

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.

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.

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.

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.

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.

By integrating microglial transcriptomics with CSF proteomics, this study reveals protein markers that distinguish early and late Alzheimer’s disease and that have the potential to improve disease tracking and prediction.

The accuracy of melanoma diagnosis can vary considerably among clinicians, impacting both patient outcomes and the performance of related AI tools. Here, the authors systematically assess interrater variability among expert pathologists reviewing histopathological images and clinical metadata of melanoma-suspicious lesions collected at eight German hospitals.

Using multi-ancestry genome-wide association study and fine-mapping, 298 loci and 36 credible genes are identified in the aetiology of bipolar disorder.

Artificial intelligence (AI) system is known to improve dermatologists’ diagnostic accuracy for melanoma. This group applies the eye-tracking technology on dermatologists when diagnosing dermoscopic images of melanomas and reports improved balanced diagnostic accuracy when using an X(explainable) AI system comparing to the standard one.

A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent risk loci. Comparisons with other psychiatric disorders and candidate gene analyses provide new insights into major depressive disorder.

Genome-wide association analyses of 41,917 bipolar disorder cases and 371,549 controls of European ancestry provide new insights into the etiology of this disorder and identify novel therapeutic leads and potential opportunities for drug repurposing.

Lipidic sponge phase crystallization yields membrane protein microcrystals that can be injected into an X-ray free electron laser beam, yielding diffraction patterns that can be processed to recover the crystal structure.

Researchers describe a mechanism capable of compressing fast and intense X-ray pulses through the rapid loss of crystalline periodicity. It is hoped that this concept, combined with X-ray free-electron laser technology, will allow scientists to obtain structural information at atomic resolutions.

Fibroblast heterogeneity in the tumor microenvironment can explain their multifaceted role in cancer. Here by single-cell transcriptomic analysis of basal cell carcinoma, squamous cell carcinoma and melanoma samples, the authors explore fibroblast heterogeneity in skin cancer and their potential to modulate the tumor-immune microenvironment.

Genome-wide analysis identifies 30 loci associated with bipolar disorder, allowing for comparisons of shared genes and pathways with other psychiatric disorders, including schizophrenia and depression.

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.

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

The genetic basis of atopic dermatitis is not fully understood. Here, the authors find 91 genetic loci associated with atopic dermatitis in a GWAS of >1million individuals, which highlight the importance of systemic immune regulation.

A new GWAS of schizophrenia (11,260 cases and 24,542 controls) and meta-analysis identifies 50 new associated loci and 145 loci in total. The common variant association signal is highly enriched in mutation-intolerant genes and in regions under strong background selection.