Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “reproducible workflows”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6Linked to original sources
PubMed2026

BioNeuralNet: a graph neural network based Multi-Omics network data analysis tool.

SUMMARY: Multi-omics data offer unprecedented insights into complex biological systems, yet their high dimensionality, sparsity, and intricate interactions pose significant analytical challenges. Network-based approaches have advanced multi-omics research by effectively capturing biologically relevant relationships among molecular features (e.g., genes, proteins, metabolites). While these methods are powerful for representing molecular interactions, there remains a need for tools specifically designed to effectively utilize these network representations across diverse downstream analyses. To fulfill this need, we introduce BioNeuralNet, a flexible and modular Python framework tailored for end-to-end network-based multi-omics data analysis. BioNeuralNet leverages Graph Neural Networks (GNNs) to learn biologically meaningful low-dimensional representations from multi-omics networks, converting these complex molecular networks into versatile embeddings. BioNeuralNet supports all major stages of multi-omics network analysis, including several network construction techniques, generation of low-dimensional representations, and a broad range of downstream analytical tasks. Its extensive utilities, including diverse GNN architectures, and compatibility with established Python packages (e.g., scikit-learn, PyTorch, NetworkX), enhance usability and facilitate quick adoption. BioNeuralNet is an open-source, user-friendly, and extensively documented framework designed to support flexible and reproducible multi-omics network analysis in precision medicine. AVAILABILITY AND IMPLEMENTATION: The BioNeuralNet library is available via The Python Package Index (PyPI). Source code, documentation, tutorials, and workflows are hosted at https://bioneuralnet.readthedocs.io. Code archived at https://doi.org/10.5281/zenodo.17503083.

Graph Neural Networks↗
PubMed2026

GENKI: A generative framework for scalable and robust metabolic kinetic modeling.

GENKI (Generative ENsemble KPI-Informed) is a variational autoencoder-based framework for large-scale kinetic modeling of metabolism. Developed for metabolic engineering applications, GENKI is designed to improve the recovery of kinetically feasible models that reproduce experimentally observed phenotypes under genetic and environmental perturbations. The framework is trained on feasible kinetic model ensembles and uses phenotype-based key performance indicators (KPIs), derived from multi-omics and bioprocess data, to label and enrich models according to their agreement with mutant and condition-specific observations. This enables targeted generation of biologically relevant parameter sets with improved predictive performance. Crucially, GENKI recovers kinetic parameter sets that jointly reproduce wild-type and multiple perturbed physiologies within a single model. We apply GENKI to large-scale kinetic models of Escherichia coli and Saccharomyces cerevisiae under enzyme perturbations and oxygen shifts. In both systems, GENKI enriches kinetic ensembles with models that more accurately reproduce experimentally observed physiologies across multiple perturbations and conditions. GENKI therefore provides a practical framework for perturbation-aware kinetic model refinement within iterative Design-Build-Test-Learn workflows.

DBTL↗
PubMed2003

Microwave synthesis solutions from Personal Chemistry.

By fulfilling the specific design criteria required for safe and reproducible microwave synthesis, Personal Chemistry introduced the first microwave system designed for organic chemistry in 2000. The principle of microwave synthesis offers 3 major benefits to chemistry development: speed, reproducibility, and a scalable approach to compound synthesis. Additionally, significant advantages of our technical solution are ease of use, safety, verified synthesis methods to enable new users, and an efficient workflow that fits the drug discovery process. To gain the greatest advantages offered by microwave synthesis, Personal Chemistry has implemented a system called Coherent Synthesis. Incorporating planning systems, automation, distributed system access, searchable databases and reaction optimisation kits, the technology has already proved itself to dramatically improve the quality of output from medicinal chemistry for lead optimisation in all the major pharmaceutical and biotech companies.

Automation↗
PubMed2026

Protocol for Duplex Sequencing of Mitochondrial DNA in Single Human Oocytes.

Oocytes are densely packed with mitochondria, the energy-producing organelles that contain their own genome, mitochondrial DNA (mtDNA). Each cell contains multiple copies of mtDNA, with copy number varying among tissue types. Oocytes possess the highest mtDNA copy number, containing hundreds of thousands of mtDNA molecules per cell. Because mitochondria are inherited exclusively through the maternal lineage, accurate detection of mtDNA variants is essential for studies of inheritance, aging, and disease. The presence of multiple mtDNA copies allows wild-type and mutant molecules to coexist within the same cell, a condition known as heteroplasmy, in which low-frequency and de novo variants may occur at frequencies below 1%. Conventional next-generation sequencing (NGS) lacks sufficient accuracy to reliably distinguish these rare variants from errors introduced during library preparation and sequencing. Here, we present a protocol for enriching mtDNA from single human oocytes using Exonuclease V to remove linear DNA, followed by duplex sequencing library preparation for highly accurate mtDNA analysis. This workflow enables error-corrected sequencing of individual oocytes, facilitating reliable detection of low-frequency mtDNA variants and analysis of heteroplasmy and de novo mutagenesis. The protocol provides a reproducible approach for investigating mitochondrial genome variation in single oocytes using Illumina-compatible sequencing platforms.

Humans↗
PubMed2003

The empty OR-process analysis and a new concept for flexible and modular use in minimal invasive surgery.

The reproducible advantages of minimal invasive surgery have led to a worldwide spread of these techniques. Nevertheless, the increasing use of technology causes problems in the operating room (OR). The workstation environment and workflow are handicapped by a great number of isolated solutions that demand a large amount of space. The Center of Excellence in Medical Technology (CEMET) was established in 2001 as an institution for a close cooperation between users, science, and manufacturers of medical devices in the State of Schleswig-Holstein, Germany. The future OR, as a major project, began with a detailed process analysis, which disclosed a large number of medical devices with different interfaces and poor standardisation as main problems. Smaller and more flexible devices are necessary, as well as functional modules located outside the OR. Only actuators should be positioned near the operation area. The future OR should include a flexible-room concept and less equipment than is in use currently. A uniform human-user interface is needed to control the OR environment. This article addresses the need for a clear workspace environment, intelligent-user interfaces, and flexible-room concept to improve the potentials in use of minimal invasive surgery.

Equipment and Supplies↗
PubMed2005

Automatic repositioning of single voxels in longitudinal 1H MRS studies.

An automatic procedure, allowing the prospective registration of brain MRI images and the acquisition of nearly identical brain volumes (coverage and orientation) in longitudinal exams, is presented. This procedure, based on a fast registration algorithm and a tailored pulse sequence, is used to reposition single voxels for 1H MRS data acquired in vivo. The impact of the repositioning method on the extent of voxel overlap and on the reproducibility of metabolite concentration measurements is studied. A statistically significant increase in voxel overlap and generally decreased short-term measurement variability (decreased coefficients of variation and increased reproducibility coefficients) are observed. Differences in the long-term variances of metabolite concentrations and concentration ratios measured using the eye and automatic repositioning scheme, however, do not reach statistical significance. The improved workflow associated with the use of the automatic repositioning process, which obviates the need for skilled operator intervention for voxel repositioning, suggests that approaches similar to the one presented here may be a standard element in tomorrow's longitudinal MRI and MRS exams.

Algorithms↗
PubMed2026

An Instrumental Optimization of a Label-Free Proteomic Method for Trace Protein Input.

Liquid chromatography-mass spectrometry (LC-MS)-based proteomics of trace-level samples, such as tens of cells or spatially resolved tissue regions, offers unique biological insights but is often constrained by the requirement for specialized, costly instrumentation. In this study, we developed a scalable workflow for the deep proteomic analysis of low- to ultralow-input samples by systematically optimizing a widely adopted Orbitrap and UHPLC platform to maximize sensitivity, precision, and throughput. This optimized workflow identified over 5600 proteins from 5 ng of peptides and 3400 proteins from 20 sorted cells, achieving a throughput of 30 analyses per day while maintaining deep proteome coverage and high quantitative reproducibility. Furthermore, by applying this method to spatially resolved proteomics, we identified over 6100 proteins from microscale regions of interest (ROIs) within a formalin-fixed, paraffin-embedded (FFPE) tissue. A data-driven normalization strategy was employed to correct for variable cellularity across tissue regions, effectively revealing intratumor heterogeneity and distinct molecular and functional signatures, including pathway activations not apparent in parallel spatial transcriptomic analysis. Ultimately, this accessible, high-performance method substantially lowers the instrumentation barrier for the deep proteomic profiling of trace-level biological samples.

Proteomics↗
PubMed2026

Integrative evidence-knowledge marker selection enhances LLM-based cell type annotation in single-cell RNA-seq analysis.

BACKGROUND: Cell type annotation is essential for gaining biological insight from single-cell RNA sequencing data, yet manual labeling remains time-consuming and difficult to reproduce. Various computational approaches have been developed to automate this process, and recent studies suggest that large language models can infer cell types with promising accuracy in single-cell analysis. However, most workflows still rely on cluster-specific markers derived from gene expression alone or manual curation. As a result, marker selection can be sensitive to statistical criteria and dataset-dependent bias, which may lead to the selection of less informative genes or missing important markers, while providing limited biological context. RESULTS: To address this limitation, we introduce CELLIA, an LLM-based workflow for automated and robust cell type annotation. CELLIA employs an integrative evidence-knowledge marker selection strategy that combines statistical differential expression criteria with curated tissue-specific marker resources to identify informative marker genes. In benchmarking analyses of 102 cell types, this approach improved agreement with manual annotations. In addition, CELLIA achieved higher agreement in subtype-level analyses of closely related immune populations and was further evaluated in a non-immune stromal subtype setting, covering 25 cell types in total. CONCLUSION: By integrating evidence-knowledge from gene expression with curated biological prior knowledge, CELLIA provides a more stable marker selection and improves the reliability of LLM-cell type annotation.

Cell type annotation↗
PubMed2001

A comparative study: conventional preparation and ThinPrep 2000 in respiratory cytology.

In order to compare and contrast conventional preparation (CP) with ThinPrep 2000 (TP) in respiratory cytology, 207 samples were divided equally and processed by the two different preparation methods, generating three CP and one TP slide per sample. No lesion identified by CP was missed by TP and there were no significant differences between TP and CP in the diagnostic categories. However, two cases of squamous cell carcinoma were detected on TP which had been classified as unsatisfactory and moderate squamous dyskaryosis, respectively, on CP. ThinPrep was found to be superior to CP in many respects as it provided standardized preparations in a greater proportion of cases and problems such as cell overlapping and background debris were markedly reduced. In several instances the diagnostic accuracy in CP was compromised by smears that were either too thick, too thin, or too scanty. Cell preservation was also better on TP when compared with CP, facilitating more accurate diagnosis and significantly reducing the primary screening and reporting time, especially of sputum samples. A major advantage of TP methodology is the fact that it facilitates optimal use of skilled cytotechnologists and streamlines the workflow in the laboratory.

Carcinoma↗
PubMed2026

Antimicrobial resistance surveillance through wastewater: methodological considerations for metagenomic approaches and public health perspectives.

Antimicrobial resistance (AMR) is a recognised global threat with substantial predicted impact on lives, agriculture, and the economy. Metagenomic sequencing is being increasingly used for AMR surveillance and detection, given its capacity for community-level AMR profiling with high-level resolution. This technology has seen an explosion of surveillance efforts and data generation; however, the variation between workflows has direct implications on the sequencing results and their interpretation. In this Personal View, we summarise aspects of the sequencing workflow that need to be considered during metagenomic study design, for meaningful and reliable population-based surveillance. We reflect on the vital role of standardisation for capturing the ground truth of AMR and data comparability and reproducibility, and in addition, review the limitations of the various phenotypic and genotypic methods of AMR detection. We further highlight complex mechanisms of resistance to antimicrobials that could hinder our ability to confidently assess the true AMR burden in the environment and those that are often overlooked during surveillance.

Metagenomics↗
PubMed2026

DNA-FISH Metaphase Spreads to Distinguish Extrachromosomal DNA from Homogeneously Staining Regions in Human Cancer Cell Lines.

Whole-genome sequencing identifies focal DNA amplifications with base-pair resolution but cannot determine whether amplified sequences reside on extrachromosomal DNA (ecDNA, also known as double minutes) or within chromosomally integrated homogeneously staining regions (HSRs). DNA fluorescence in situ hybridization (DNA-FISH) metaphase spreads remain the gold standard for distinguishing these amplification states at single-cell resolution. Here, we present a detailed protocol for DNA-FISH metaphase spreads using human cancer cell lines, encompassing cell culture, metaphase arrest, hypotonic treatment, fixation, chromosome spreading, fluorescent probe hybridization, and fluorescence imaging. The protocol incorporates intermediate quality-control steps to verify successful chromosome dispersion and optimize metaphase spread quality, making the workflow accessible to laboratories without specialized cytogenetics expertise. Results demonstrate clear visualization of ecDNA and HSR amplification states using locus-specific probes and illustrate common technical artifacts that can affect interpretation. This protocol provides a robust and reproducible approach for studying the structural organization of oncogene amplification in cancer cells.

Humans↗
PubMed2026

DNA-FISH Metaphase Spreads to Distinguish Extrachromosomal DNA from Homogeneously Staining Regions in Human Cancer Cell Lines.

UNLABELLED: Whole-genome sequencing identifies focal DNA amplifications with base-pair resolution but cannot determine whether amplified sequences reside on extrachromosomal DNA (ecDNA, also known as double minutes) or within chromosomally integrated homogeneously staining regions (HSRs). DNA fluorescence in situ hybridization (DNA-FISH) metaphase spreads remain the gold standard for distinguishing these amplification states at single-cell resolution. Here, we present a detailed protocol for DNA-FISH metaphase spreads using human cancer cell lines, encompassing cell culture, metaphase arrest, hypotonic treatment, fixation, chromosome spreading, fluorescent probe hybridization, and fluorescence imaging. The protocol incorporates intermediate quality-control steps to verify successful chromosome dispersion and optimize metaphase spread quality, making the workflow accessible to laboratories without specialized cytogenetics expertise. Results demonstrate clear visualization of ecDNA and HSR amplification states using locus-specific probes and illustrate common technical artifacts that can affect interpretation. This protocol provides a robust and reproducible approach for studying the structural organization of oncogene amplification in cancer cells. SUMMARY: We report a DNA-FISH metaphase spread protocol that visually detects locus copy number and location within the genome. This approach enables single-cell resolution of amplification states, specifically in cancer cell lines containing extrachromosomal DNA and homogeneously staining regions.

Journal Article↗
PubMed2020

Genomic Analysis of Circulating Tumor Cells at the Single-Cell Level.

Circulating tumor cells (CTCs) have a great potential for noninvasive diagnosis and real-time monitoring of cancer. A comprehensive evaluation of four whole genome amplification (WGA)/next-generation sequencing workflows for genomic analysis of single CTCs, including PCR-based (GenomePlex and Ampli1), multiple displacement amplification (Repli-g), and hybrid PCR- and multiple displacement amplification-based [multiple annealing and loop-based amplification cycling (MALBAC)] is reported herein. To demonstrate clinical utilities, copy number variations (CNVs) in single CTCs isolated from four patients with squamous non-small-cell lung cancer were profiled. Results indicate that MALBAC and Repli-g WGA have significantly broader genomic coverage compared with GenomePlex and Ampli1. Furthermore, MALBAC coupled with low-pass whole genome sequencing has better coverage breadth, uniformity, and reproducibility and is superior to Repli-g for genome-wide CNV profiling and detecting focal oncogenic amplifications. For mutation analysis, none of the WGA methods were found to achieve sufficient sensitivity and specificity by whole exome sequencing. Finally, profiling of single CTCs from patients with non-small-cell lung cancer revealed potentially clinically relevant CNVs. In conclusion, MALBAC WGA coupled with low-pass whole genome sequencing is a robust workflow for genome-wide CNV profiling at single-cell level and has great potential to be applied in clinical investigations. Nevertheless, data suggest that none of the evaluated single-cell sequencing workflows can reach sufficient sensitivity or specificity for mutation detection required for clinical applications.

Carcinoma, Non-Small-Cell Lung↗
PubMed2026

RUMINA: high-throughput deduplication of unique molecular identifiers for amplicon and whole-genome sequencing with enhanced error correction.

MOTIVATION: Unique molecular identifiers (UMIs) are widely used in next-generation sequencing to enable accurate molecular counting and error correction. However, challenges remain in accurately collapsing UMI clusters, especially when read counts are low or sparse read clusters arise from barcode sequencing errors. RESULTS: We present RUMINA, a Rust-based pipeline for UMI-aware deduplication and error correction, optimized for both amplicon and shotgun sequencing. RUMINA supports multiple UMI cluster strategies, alongside majority-rule read selection independent of mapping quality, as well as discrete handling of 1-2 read clusters, paired-end merging, and read-length stratification. Benchmarking using simulated HIV population sequencing data and real-world iCLIP and TCR datasets showed that RUMINA improves ultra-low frequency SNV detection (0.01%-1%), reduces false positives, enhances reproducibility, and processes sequencing data up to 10-fold faster than existing tools. By integrating UMI- and sequence-level correction in a high-performance framework, RUMINA offers a fast, scalable, and robust solution for UMI-enabled sequencing workflows. AVAILABILITY AND IMPLEMENTATION: RUMINA is implemented in Rust and distributed as open-source code and precompiled binaries. Source code and installation instructions are available at https://github.com/greninger-lab/rumina. Documentation associated with this manuscript is available at https://github.com/greninger-lab/rumina_paper.

High-Throughput Nucleotide Sequencing↗
PubMed2006

Gemvid, an open source, modular, automated activity recording system for rats using digital video.

BACKGROUND: Measurement of locomotor activity is a valuable tool for analysing factors influencing behaviour and for investigating brain function. Several methods have been described in the literature for measuring the amount of animal movement but most are flawed or expensive. Here, we describe an open source, modular, low-cost, user-friendly, highly sensitive, non-invasive system that records all the movements of a rat in its cage. METHODS: Our activity monitoring system quantifies overall free movements of rodents without any markers, using a commercially available CCTV and a newly designed motion detection software developed on a GNU/Linux-operating computer. The operating principle is that the amount of overall movement of an object can be expressed by the difference in total area occupied by the object in two consecutive picture frames. The application is based on software modules that allow the system to be used in a high-throughput workflow. Documentation, example files, source code and binary files can be freely downloaded from the project website at http://bioinformatics.org/gemvid/. RESULTS: In a series of experiments with objects of pre-defined oscillation frequencies and movements, we documented the sensitivity, reproducibility and stability of our system. We also compared data obtained with our system and data obtained with an Actiwatch device. Finally, to validate the system, results obtained from the automated observation of 6 rats during 7 days in a regular light cycle are presented and are accompanied by a stability test. The validity of this system is further demonstrated through the observation of 2 rats in constant dark conditions that displayed the expected free running of their circadian rhythm. CONCLUSION: The present study describes a system that relies on video frame differences to automatically quantify overall free movements of a rodent without any markers. It allows the monitoring of rats in their own environment for an extended period of time. By using a low-cost, open source hardware/software solution, laboratories can greatly simplify their data acquisition and analysis pipelines and improve their workload.

Journal Article↗
PubMed2004

Simultaneous runs of the Bayer VERSANT HIV-1 version 3.0 and HCV bDNA version 3.0 quantitative assays on the system 340 platform provide reliable quantitation and improved work flow.

Branched DNA (bDNA) assays to quantify human immunodeficiency virus type 1 (HIV-1) and hepatitis C virus (HCV) consist of three distinct steps, including sample processing, hybridization, and detection, and utilize the System 340 platform for plate incubation and washing. Sample processing differs: HIV-1 from 1 ml of plasma is concentrated by high-speed centrifugation, whereas HCV plasma or serum samples are used without concentration. The first step of hybridization involves viral lysis at 63 degrees C: HIV-1 is performed in a heat block, whereas HCV is performed in System 340. The remaining hybridization and detection steps are similar for HIV-1 and HCV and executed on System 340. In the present study, the HIV-1 bDNA assay was adapted for viral lysis in the System 340 platform. The adaptation, test method 2, includes a 20-s vortex of concentrated viral pellet and lysis working solution, transfer of viral lysate to the 96-well capture plate, and transfer to System 340 programmed for HCV assay specifications. With test method 2, specificity and quantification were within assay specifications. HCV bDNA methodology remains unchanged. Hence, an HIV-1 and an HCV bDNA can be run simultaneously on System 340. With simultaneous testing, laboratories can run full plates, as well as combinations of full and partial plates. Also, simultaneous HIV-1 and HCV bDNA permits labor consolidation and improved workflow while maintaining multitasking and rapid patient result turnaround.

DNA, Viral↗
PubMed2005

Evaluation of multidimensional (ion-exchange/reversed-phase) protein separations using linear and step gradients in the first dimension.

The performance characteristics of multidimensional liquid chromatographic protein separations were evaluated using on-line electrospray mass detection, and a novel workflow for automated LC/MS data processing. Two-dimensional ion exchange/reversed-phase LC separations of Escherichia coli cytosol were conducted using either a continuous linear or discontinuous step gradient in the first dimension. Chromatographic profiles of the top 100 most abundant components were characterized to assess overall separation reproducibility within each mode, and to characterize differences in component distribution between the two modes of operation. Analysis of the resulting data indicates that multidimensional separations of complex protein mixtures can be done reproducibly. Furthermore, under the conditions employed within this study, a linear first dimension gradient was more effective at fractionating the protein mixture, distributing fewer major components to multiple second dimension cycles than an equivalent step gradient. The application of on line mass spectrometry, and automated processing of the resulting data, proved valuable for producing component level analysis of multidimensional protein separations.

Chromatography, Ion Exchange↗