Dick de Ridder

When do hybrid models help? Combining mechanistic modelling and machine learning to predict gene regulatory network dynamics

This study investigates when combining mechanistic and machine learning models improves predictions of gene regulatory network dynamics using synthetic data.

Identification and Classification of Expressed Orphan Genes, Spurious Orphan Genes, and Conserved Genes in the Human Gut Microbiome

The paper distinguishes expressed orphan genes from spurious ones and conserved genes in the human gut microbiome using metatranscriptomic data and machine learning.

An integrative single-cell and spatial transcriptomics atlas highlights candidate regulatory factors in the development of gerbera capitulum

The paper develops an integrative single-cell and spatial transcriptomics atlas of Gerbera capitulum development, identifying candidate regulatory factors like GAGL12 involved in vasculature development.

RdRpCATCH: A unified resource for RNA virus discovery using viral RNA-dependent RNA polymerase profile Hidden Markov models

RdRpCATCH consolidates multiple RdRp pHMM databases into a single platform for RNA virus discovery and taxonomic annotation, improving accessibility and performance.

Acquiring Improved Protein Variants With Probabilistic Preferential Learning

This paper introduces a probabilistic preferential learning model for variant effect prediction, showing that uncertainty-aware strategies improve acquisition performance on single-mutation datasets.

Genus-wide homologous recombination of tail fibers maintains tailocin diversity in Pectobacterium

The paper investigates the evolutionary dynamics of carotovoricin in Pectobacterium, finding that tail fiber gene exchange maintains diversity and influences community interactions.

MoGAAAP: A modular Snakemake workflow for automated genome assembly and annotation with quality assessment

MoGAAAP automates genome assembly and annotation using HiFi and other long-read data, producing quality assessments for comparative genomics.

Three novel genomes broaden the wild side of the Capsicum pangenome

This paper presents three new Capsicum genomes, expands the pangenome framework, and identifies genetic diversity and gene loci relevant to capsaicinoid biosynthesis.

A generic pipeline for CADD score generation: chickenCADD and turkeyCADD

The paper introduces a pipeline for generating CADD scores across species, presenting updated chickenCADD and newly generated turkeyCADD scores.

Predicting protein variant properties with electrostatic representations

This study evaluates whether electrostatic representations improve variant effect prediction models using DMS data, but finds no advantage over evolutionary models.

Two high-quality rose genomes underpin a novel Rosa pangenome to advance rose genomics, phylogenetics, and breeding

This study presents two high-quality rose genomes and constructs a Rosa pangenome to explore genetic diversity, evolution, and breeding potential in the genus Rosa.

Pangenomics to understand prophage dynamics in the Pectobacterium genus and the radiating lineages of P. brasiliense

The paper studies prophage dynamics in Pectobacterium species using a pangenome approach, finding that prophages contribute significantly to genome evolution and lineage diversification.

Exploring intra- and intergenomic variation in haplotype-resolved pangenomes

The paper introduces PanTools, a ploidy-aware pangenome analysis tool, and demonstrates its application to potato and apple genomes, revealing high allelic diversity and structural variants.

BADDADAN: Mechanistic Modelling of Time Series Gene Module Expression

BADDADAN models gene module dynamics under stress using machine learning and ODEs, demonstrating its application on A. thaliana datasets to recover known insights and propose new hypotheses.

Lactuca super-pangenome reduces bias towards reference genes in lettuce research

This study constructs a lettuce super-pangenome to reduce bias in reference genes, identifying novel QTLs for disease resistance and origins of non-reference resistance loci from wild relatives.

Expanding the Triangle of U: The genome assembly of Hirschfeldia incana provides insights into chromosomal evolution, phylogenomics and high photosynthesis-related traits

This paper presents an improved genome assembly of Hirschfeldia incana, revealing insights into chromosomal evolution, phylogenomics, and genes related to high photosynthesis traits.

Enzyme structure correlates with variant effect predictability

The paper shows that structural features of enzymes influence the predictability of variant effects, with consistent dependencies across multiple models.

Pollen sequencing reveals barriers and aberrant patterns of recombination in interspecific tomato hybrids

This study uses pollen sequencing to analyze recombination patterns in tomato hybrids, identifying coldspots and their association with transposable elements and gene complexes, and proposes strategies to overcome recombination barriers.

baseLess: Lightweight detection of sequences in raw MinION data

baseLess detects target sequences in raw MinION data using small neural networks, achieving accurate classification on low-cost hardware.

Revealing determinants of translation efficiency via whole-gene codon randomisation and machine learning

This study uses codon randomisation and machine learning to show that the first 8 codons of a gene strongly predict protein production levels in E. coli.

The genome sequence of Hirschfeldia incana, a species with high photosynthetic light-use efficiency

The paper presents a reference genome assembly of Hirschfeldia incana, showing its high photosynthetic efficiency compared to related Brassicaceae species and identifying genomic features potentially contributing to this trait.

OptiDiff: structural variation detection from single optical mapping reads

OptiDiff detects and classifies homozygous and heterozygous structural variations from optical mapping data with better performance than existing methods at low coverage.

Chop-n-drop: in silico assessment of a novel single-molecule protein fingerprinting method employing fragmentation and nanopore detection

The paper evaluates a nanopore-based method for single-molecule protein identification, showing high accuracy and robustness in simulated conditions.

Signal-based optical map alignment

This paper introduces two open-source tools for processing and aligning optical mapping data to improve genome assembly and data utilization.

Fast and adaptive protein structure representations for machine learning

The paper introduces a fast structure aligner using rotation-invariant shape-mers for protein structures, enabling efficient machine learning analysis of functional and structural similarities.

Integrating structure-based machine learning and co-evolution to investigate specificity in plant sesquiterpene synthases

The paper predicts precursor cation specificity in plant sesquiterpene synthases using machine learning and co-evolution analysis, identifying key residues for enzyme function.

BiG-SLiCE: A Highly Scalable Tool Maps the Diversity of 1.2 Million Biosynthetic Gene Clusters

BiG-SLiCE clusters 1.2 million biosynthetic gene clusters from microbial genomes and MAGs efficiently, enabling analysis of secondary metabolic diversity and novel chemistry.

Evolutionarily conserved non-protein-coding regions in the chicken genome harbor functionally important variation

The paper identifies functionally important variants in conserved non-protein-coding regions of the chicken genome using a variant effect prediction tool called chCADD.

Geometricus Represents Protein Structures as Shape-mers Derived from Moment Invariants

Geometricus embeds protein structures into fixed-length vectors using shape-mers derived from 3D moment invariants, enabling tasks like structure similarity search and clustering.

CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

CAPICE is a machine learning method that prioritizes pathogenic variants in exomes, outperforming existing tools for rare and ultra-rare variants.