Biology subjects

van den Beek, M.

Publications and source records attributed to van den Beek, M..

9 recordsLinked to original sources

bioRxiv2026

Verifiable Agentic Science on Public Infrastructure

Autonomous artificial intelligence agents are transforming the practice of science. Across every discipline, researchers are handing data analysis to coding agents that can design and execute complex studies from a single prompt. Yet this revolution carries a threat. When agents improvise in local environments, they leave no verifiable record, ultimately risking a wave of irreproducible science. Solving this crisis requires moving agentic science onto public infrastructure where every action leaves an examinable trail. Here we connect autonomous coding agents to shared computing resources, turning ephemeral prompts into auditable scientific records. After showing that 30 unguided local agents splinter into 18 incompatible pipelines on the same dataset, we conduct an agentic reproduction and discovery study on a large scale---reproducing a large, diverse array of studies with every workflow, history, and intermediate dataset publicly accessible. This complete provenance trail exposes unstated modeling choices, reference mismatches, and subsampled tutorial inputs in published studies, and establishes a new foundation where human scientists can understand, steer, and trust AI-driven discovery.

bioinformatics↗

bioRxiv2023

Scalable, accessible, and reproducible reference genome assembly and evaluation in Galaxy

Improvements in genome sequencing and assembly are enabling high-quality reference genomes for all species. However, the assembly process is still laborious, computationally and technically demanding, lacks standards for reproducibility, and is not readily scalable. Here we present the latest Vertebrate Genomes Project assembly pipeline and demonstrate that it delivers high-quality reference genomes at scale across a set of vertebrate species arising over the last [~]500 million years. The pipeline is versatile and combines PacBio HiFi long-reads and Hi-C-based haplotype phasing in a new graph-based paradigm. Standardized quality control is performed automatically to troubleshoot assembly issues and assess biological complexities. We make the pipeline freely accessible through Galaxy, accommodating researchers even without local computational resources and enhanced reproducibility by democratizing the training and assembly process. We demonstrate the flexibility and reliability of the pipeline by assembling reference genomes for 51 vertebrate species from major taxonomic groups (fish, amphibians, reptiles, birds, and mammals).

bioinformatics↗

bioRxiv2022

Planemo: a command-line toolkit for developing, deploying, and executing scientific data analyses

There are thousands of well-maintained high-quality open-source software utilities for all aspects of scientific data analysis. For over a decade, the Galaxy Project has been providing computational infrastructure and a unified user interface for these tools to make them accessible to a wide range of researchers. In order to streamline the process of integrating tools and constructing workflows as much as possible, we have developed Planemo, a software development kit for tool and workflow developers and Galaxy power users. Here we outline Planemos implementation and describe its broad range of functionality for designing, testing and executing Galaxy tools, workflows and training material. In addition, we discuss the philosophy underlying Galaxy tool and workflow development, and how Planemo encourages the use of development best practices, such as test-driven development, by its users, including those who are not professional software developers. Planemo is a mature project widely used within the Galaxy community which has been downloaded over 80,000 times.

bioinformatics↗

bioRxiv2021

Freely accessible ready to use global infrastructure for SARS-CoV-2 monitoring

The COVID-19 pandemic is the first global health crisis to occur in the age of big genomic data.Although data generation capacity is well established and sufficiently standardized, analytical capacity is not. To establish analytical capacity it is necessary to pull together global computational resources and deliver the best open source tools and analysis workflows within a ready to use, universally accessible resource. Such a resource should not be controlled by a single research group, institution, or country. Instead it should be maintained by a community of users and developers who ensure that the system remains operational and populated with current tools. A community is also essential for facilitating the types of discourse needed to establish best analytical practices. Bringing together public computational research infrastructure from the USA, Europe, and Australia, we developed a distributed data analysis platform that accomplishes these goals. It is immediately accessible to anyone in the world and is designed for the analysis of rapidly growing collections of deep sequencing datasets. We demonstrate its utility by detecting allelic variants in high-quality existing SARS-CoV-2 sequencing datasets and by continuous reanalysis of COG-UK data. All workflows, data, and documentation is available at https://covid19.galaxyproject.org.

bioinformatics↗

bioRxiv2021

Fast and accurate genome-wide predictions and structural modeling of protein-protein interactions using Galaxy

Protein-protein interactions play a crucial role in almost all cellular processes. Identifying interacting proteins reveals insight into living organisms and yields novel drug targets for disease treatment. Here, we present a publicly available, automated pipeline to predict genome-wide protein-protein interactions and produce high-quality multimeric structural models. Application of our method to the Human and Yeast genomes yield protein-protein interaction networks similar in quality to common experimental methods. We identified and modeled Human proteins likely to interact with the papain-like protease of SARS-CoV2s non-structural protein 3 (Nsp3). We also produced models of SARS-CoV2s spike protein (S) interacting with myelin-oligodendrocyte glycoprotein receptor (MOG) and dipeptidyl peptidase-4 (DPP4). The presented method is capable of confidently identifying interactions while providing high-quality multimeric structural models for experimental validation. The interactome modeling pipeline is available at usegalaxy.org and usegalaxy.eu.

genomics↗

bioRxiv2020

Expanding the Galaxy's reference data

SummaryProperly and effectively managing reference datasets is an important task for many bioinformatics analyses. Refgenie is a reference asset management system that allows to easily organize, retrieve, and share such datasets. Here, we describe the integration of refgenie into the Galaxy platform. Server administrators are able to configure Galaxy to make use of reference datasets made available on a refgenie instance. Additionally, a Galaxy Data Manager tool has been developed to provide a graphical interface to refgenies remote reference retrieval functionality. A large collection of reference datasets has also been made available using the CVMFS repository from GalaxyProject.org, with mirrors across the United States, Canada, Europe, and Australia, enabling easy use outside of Galaxy. Availability and implementationThe ability of Galaxy to use refgenie assets was added to the core Galaxy framework in version 20.05, which is available from https://github.com/galaxyproject/galaxy under the Academic Free License version 3.0. The refgenie Data Manager tool can be installed via the Galaxy ToolShed, with source code managed at https://github.com/BlankenbergLab/galaxy-tools-blankenberg/tree/main/data_managers/data_manager_refgenie_pull and released using an MIT license.

bioinformatics↗

bioRxiv2020

Evolution and genomic signatures of spontaneous somatic mutation in Drosophila intestinal stem cells

Spontaneous mutations can alter tissue dynamics and lead to cancer initiation. While large-scale sequencing projects have illustrated processes that influence somatic mutation and subsequent tumour evolution, the mutational dynamics operating in the very early stages of cancer development are currently not well understood. In order to explore mutational dynamics in the early stages of cancer evolution we exploited neoplasia arising spontaneously in the Drosophila intestine. We analysed whole-genome sequencing data through the development of a dedicated bioinformatic pipeline to detect structural variants, single nucleotide variants, and indels. We found neoplasia formation to be driven largely through the inactivation of Notch by structural variants, many of which involve highly complex genomic rearrangements. Strikingly, the genome-wide mutational burden of neoplasia - at six weeks of age - was found to be similar to that of several human cancers. Finally, we identified genomic features associated with spontaneous mutation and defined the evolutionary dynamics and mutational landscape operating within intestinal neoplasia over the short lifespan of the adult fly. Our findings provide unique insight into mutational dynamics operating over a short time scale in the genetic model system, Drosophila melanogaster.

genomics↗

bioRxiv2018

Galaxy-Kubernetes integration: scaling bioinformatics workflows in the cloud

Making reproducible, auditable and scalable data-processing analysis workflows is an important challenge in the field of bioinformatics. Recently, software containers and cloud computing introduced a novel solution to address these challenges. They simplify software installation, management and reproducibility by packaging tools and their dependencies. In this work we implemented a cloud provider agnostic and scalable container orchestration setup for the popular Galaxy workflow environment. This solution enables Galaxy to run on and offload jobs to most cloud providers (e.g. Amazon Web Services, Google Cloud or OpenStack, among others) through the Kubernetes container orchestrator. AvailabilityAll code has been contributed to the Galaxy Project and is available (since Galaxy 17.05) at https://github.com/galaxyproject/ in the galaxy and galaxy-kubernetes repositories. https://public.phenomenal-h2020.eu/ is an example deployment. Suppl. InformationSupplementary Files are available online. Contactpmoreno@ebi.ac.uk, European Molecular Biology Laboratory, EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SD, UK, Tel: +44-1223-494267, Fax: +44-1223-484696.

bioinformatics↗

bioRxiv2018

Dual-layer transposon repression in heads of Drosophila melanogaster

piRNA-mediated repression of transposable elements (TE) in the germline limits the accumulation of heritable mutations caused by their transposition in the genome. It is not clear whether the piRNA pathway plays a functional role in adult, non-gonadal tissues in Drosophila melanogaster. To address this question, we first analyzed the small RNA content of adult Drosophila melanogaster heads. We found that varying amount of piRNA-sized, ping-pong positive molecules in heads correlates with contamination by gonadal tissue during RNA extraction, suggesting that most of piRNAs detected in head sequencing libraries originate from gonads. We next sequenced the heads of wild type and piwi mutants to address whether piwi loss of function would affect the low amount of piRNA-sized, ping-pong negative molecules that are still detected in heads hand-checked to avoid gonadal contamination. We find that loss of piwi does not affect significantly these 24-28 RNA molecules. Instead, we observe increased siRNA levels against the majority of Drosophila transposable element families. To determine the effect of this siRNA level change on transposon expression, we sequenced the transcriptome of wild type, piwi, dicer-2 and piwi, dicer-2 double-mutant fly heads. We find that RNA expression levels of the majority of TE families in piwi or dicer-2 mutants remain unchanged and that TE transcript abundance increases significantly only in piwi, dicer-2 double-mutants. These results lead us to suggest a dual-layer model for TE repression in adult somatic tissues. Piwi-mediated transcriptional gene silencing (TGS) established during embryogenesis constitutes the first layer of TE repression whereas Dicer-2-dependent siRNA-mediated post-transcriptional gene silencing (PTGS) provide a backup mechanism to repress TEs that escape silencing by piwi-mediated TGS.

genetics↗