Databases

Studies of cell heterogeneity in white matter in primates have been limited to date. Here the authors describe a marmoset brain cell atlas that bridges rodent and human data, revealing strong gray-white matter glial segregation.

There is a broad range of research available on the relationship between food security and mental health. Here the authors carry out a systematic mapping of evidence on food security and nutrition related to mental health and identifies trends in themes, setting, and study design over the 20 year period studied.

Pigs are important large animal models for biomedical research. Here, the authors construct a single-cell landscape of pig tissues, unravelling the phenotypic heterogeneity of blood endothelial cells in adipose tissues and the evolutionally conserved regulons of microglia in brains.

A comprehensive data portal to explore plant regulomes is still unavailable. Here, the authors develop a web-based platform ChIP-Hub in the ENCODE standards and demonstrate its applications in the identification of hierarchical regulatory network, tissue-specific chromatin dynamics, putative enhancers and chromatin states.

This paper describes the ‘4DN Data Portal’ that hosts data generated by the 4D Nucleome network, including Hi-C and other chromatin conformation capture assays, as well as various sequencing-based and imaging-based assays. Raw data have been uniformly processed to increase comparability and the portal is implemented with visualization tools to browse the data without download.

Here the authors present KIDS, a knowledge graph integration and phenotypic prediction framework. When applied on antibiotic data, it identifies 6 novel antibiotic resistant E. coli genes that the authors subsequently validate.

Here, we present TP-DB; a pattern-based search engine based on 1.67 million helices from the Protein Database (PDB). We demonstrate the utility of TP-DB in identifying microbe-specific antigens, as well as the design of antimicrobial peptides and Protein-protein interaction blockers.

There is an unmet need for adaptable tools allowing biomedical researchers to employ network-based drug repurposing approaches for their individual use cases. Here, the authors close this gap with NeDRex, an integrative and interactive platform.

Local gene co-expression is found throughout the genome, but systematic analysis of these co-expressed genes is needed. Here, the authors identify local co-expressed genes in 49 tissues and characterize the genetic variants which may affect their expression and contribute to disease.

High-quality gRNA activity data is needed for accurate on-target efficiency predictions. Here the authors generate activity data for over 10,000 gRNA and build a deep learning model CRISPRon for improved performance predictions.

Single-nucleotide variants in enhancers or promoters may affect gene transcription by altering transcription factor binding sites. Here the authors present a meta-analysis empowered by a new statistical method covering thousands of ChIP-Seq experiments resulting in the identification of more than 500 thousand allele-specific binding (ASB) events in the human genome.

Sarcomas are morphologically heterogeneous tumours rendering their classification challenging. Here the authors developed a classifier using DNA methylation data from several soft tissue and bone sarcoma subtypes, which has the potential to improve classification for research and clinical purposes.

The IMEx consortium provides one of the largest resources of curated, experimentally verified molecular interaction data. Here, the authors review how IMEx evolved into a fundamental resource for life scientists and describe how IMEx data can support biomedical research.

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.

Collision cross section (CCS) information can aid the annotation of unknown metabolites. Here, the authors optimize the machine-learning based prediction of metabolite CCS values and curate a 1.6 million compound CCS atlas, improving annotation accuracy and coverage for known and unknown metabolites.

Schulz et al. systematically benchmark performance scaling with increasingly sophisticated prediction algorithms and with increasing sample size in reference machine-learning and biomedical datasets. Complicated nonlinear intervariable relationships remain largely inaccessible for predicting key phenotypes from typical brain scans.

Single-cell RNA-seq (scRNA-seq) is being widely used to resolve cellular heterogeneity. Here, the authors present a cell-querying method built on a neural network-based generative model and a customized cell-to-cell similarity metric.

The low curation of existing nanomaterials’s databases is limiting their application in modeling studies. Here the authors report a publicly available nanomaterial database that contains annotated nanostructures of diverse nanomaterials immediately available for modeling research studies.

Reference databases are essential for studies on host-microbiota interactions. Here, the authors present the construction of VIRGO, a human vaginal non-redundant gene catalog, which represents a comprehensive resource for taxonomic and functional profiling of vaginal microbiomes from metagenomic and metatranscriptomic datasets.

The authors previously developed the Protein Common Interface Database (ProtCID), which compares and clusters the interfaces of pairs of full-length protein chains with defined Pfam domain architectures in different PDB entries to identify biological assemblies. Here the authors extend ProtCID to the clustering of domain-domain interactions that also allows analyzing domain interactions with peptides, nucleic acids, and ligands.

Most databases of genotype-phenotype associations are manually curated. Here, Kuleshov et al. describe a machine curation system that extracts such relationships from the GWAS literature and synthesizes them into a structured knowledge base called GWASkb that can complement manually curated databases.

To be able to use infectious disease next generation sequencing as a diagnostic tool, appropriate reference datasets are required. Here, Sichtig et al. describe FDA-ARGOS, a reference database for high-quality microbial reference genomes, and demonstrate its utility on the example of two use cases.

Glycomics is gaining momentum in basic, translational and clinical research. Here, the authors review current reporting standards and analysis tools for mass-spectrometry-based glycomics, and propose an e-infrastructure for standardized reporting and online deposition of glycomics data.

Questions of causality are ubiquitous in Earth system sciences and beyond, yet correlation techniques still prevail. This Perspective provides an overview of causal inference methods, identifies promising applications and methodological challenges, and initiates a causality benchmark platform.

Genetic variants might exert their functional effects via influencing molecular interaction. Here, the authors present a resource featuring almost 28,000 annotations describing the effect of small sequence changes on physical protein interactions, curated by IMEx Consortium curators.

Short-tandem repeats (STR), similar to single nucleotide polymorphisms (SNP), contribute to complex traits, but their ascertainment by next-generation sequencing is costly. Here, Saini et al. provide a SNP+STR haplotype reference panel that allows imputation of STRs from SNP array data.

Proteoforms arise as protein isoforms or as protein haplotypes, which are the result of genetic variation. Here, the authors develop Haplosaurus, a database that computes protein haplotypes genome-wide from existing genotype data and analyse protein haplotype variability in the 1000 Genomes dataset.

Data sharing is recognized as a way to promote scientific collaboration and reproducibility, but some are concerned over whether research based on shared data can achieve high impact. Here, the authors show that neuroimaging papers using shared data are no less likely to appear in top-ranked journals.

Here, Libertini and colleagues devise a computation tool that can analyze whole-genome bisulfite sequencing (WGBS) data to recover of ∼30% of the lost differential methylation position information. They use COMETgazer and COMETvintage to analyze 13 diffferent methylome data to demonstrate their performance.