SEARCH · PubMed Health

Results for “Workflow”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

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

At least 343 records · Page 19Linked to original sources

PubMed2026

Metatranscriptomic analysis of viral sequences associated with Culex nigripalpus at an Alabama aquaculture site.

Mosquitoes associated with aquaculture habitats can harbor diverse viruses, yet the viromes of many locally abundant species remain poorly characterized. At an aquaculture-associated site in Auburn, Alabama, we surveyed mosquito populations and found Culex nigripalpus to be the dominant species collected. To characterize viruses associated with this mosquito, we performed RNA-seq on pooled female Cx. nigripalpus and compared complementary bioinformatic workflows for viral detection and genome recovery. One workflow removed host-associated reads by mapping to the closest available mosquito reference genome prior to assembly, whereas a second workflow used fully de novo assembly and viral database annotation. Additional protein-level filtering, cross-workflow comparison, and comparison of Trinity and rnaSPAdes assemblies were used to prioritize well-supported viral candidates. Across the original analyses, 16 submitted accessions corresponding to 12 collapsed virus/name groups were recovered, including Merida virus, Hubei mosquito virus 5, Zhejiang mosquito virus, Hubei virga-like virus 3, Rinkaby virus, Elemess virus, Qingnian mosquito virus, Serbia narna-like virus 2, XiangYun narna-levi-like virus 8, Ecclesville picorna-like virus, and baculovirus-like fragments. Several candidates were supported across multiple workflows, while others were recovered only under specific analytical conditions, indicating that candidate recovery was influenced by assembly and filtering choices. Selected viral contigs were independently supported by RT-PCR amplification. Overall, these results provide a first characterization of viral sequences associated with Cx. nigripalpus from an Alabama aquaculture-associated site and show that comparison across assembly and filtering strategies helped prioritize the most consistently supported viral candidates.

Animals↗

PubMed2026

Human-AI Interaction With AI-Assisted Tumor Overlays in Pediatric Whole-Body Magnetic Resonance Imaging: Exploratory Reader Study.

BACKGROUND: AI tools have the potential to enhance personalized clinical care, particularly in radiology. However, their integration into clinical workflows remains complex, especially in pediatric oncology, where early cancer detection is critical. Children with Li-Fraumeni syndrome (LFS), a rare cancer predisposition disorder, undergo regular surveillance whole-body magnetic resonance imaging (wbMRI), which presents an opportunity for AI-assisted tumor detection. OBJECTIVE: We evaluated the feasibility of an AI-assisted overlay for highlighting tumor-like regions in pediatric surveillance wbMRI and explored how access to the overlay influenced radiologist workflow, candidate-lesion marking behavior, follow-up recommendations, and perceived workload. METHODS: We developed a patch-based AI segmentation model trained on augmented 2D slices from 675 surveillance wbMRI volumes of pediatric patients with LFS. The model was designed to highlight regions with high tumor probability. A reader study was conducted with 2 radiologists who independently reviewed wbMRI cases both with and without AI assistance. We measured evaluation time, number and location of reader-marked candidate lesions, type of follow-up recommendation, and subjective feedback using structured questionnaires. RESULTS: AI assistance altered interpretation workflows for both radiologists, with mixed effects. On average, the time required to evaluate each case increased when using the AI tool for both radiologists. However, one radiologist had an increase in the number of candidate lesion locations selected with the tool, and one had a decrease in the number of candidate lesion locations selected with the tool. Subjective feedback indicated that one of the radiologists reported lower mental demand with the AI tool, while both radiologists reported lower stress with the AI tool. Interrater variability was evident, underscoring the need for personalized calibration of AI tools. CONCLUSIONS: AI-assisted wbMRI interpretation can improve tumor detection in pediatric cancer surveillance by reducing false negatives. However, its influence on workflow efficiency and interradiologist variability highlights the importance of careful implementation. Successful integration requires addressing challenges such as improving the predictive precision of AI models, offering intuitive end-user designs and instructions, and building trust in AI outputs. AI outputs can influence workflow and behavior in reader-specific ways. Clinical translation will require larger, randomized, multireader studies and model refinement to reduce false positives and quantify lesion-level reader performance. This can help ensure better patient outcomes in addition to reduced clinician burnout.

Humans↗

PubMed2004

DietPal: a Web-based dietary menu-generating and management system.

BACKGROUND: Attempts in current health care practice to make health care more accessible, effective, and efficient through the use of information technology could include implementation of computer-based dietary menu generation. While several of such systems already exist, their focus is mainly to assist healthy individuals calculate their calorie intake and to help monitor the selection of menus based upon a prespecified calorie value. Although these prove to be helpful in some ways, they are not suitable for monitoring, planning, and managing patients' dietary needs and requirements. This paper presents a Web-based application that simulates the process of menu suggestions according to a standard practice employed by dietitians. OBJECTIVE: To model the workflow of dietitians and to develop, based on this workflow, a Web-based system for dietary menu generation and management. The system is aimed to be used by dietitians or by medical professionals of health centers in rural areas where there are no designated qualified dietitians. METHODS: First, a user-needs study was conducted among dietitians in Malaysia. The first survey of 93 dietitians (with 52 responding) was an assessment of information needed for dietary management and evaluation of compliance towards a dietary regime. The second study consisted of ethnographic observation and semi-structured interviews with 14 dietitians in order to identify the workflow of a menu-suggestion process. We subsequently designed and developed a Web-based dietary menu generation and management system called DietPal. DietPal has the capability of automatically calculating the nutrient and calorie intake of each patient based on the dietary recall as well as generating suitable diet and menu plans according to the calorie and nutrient requirement of the patient, calculated from anthropometric measurements. The system also allows reusing stored or predefined menus for other patients with similar health and nutrient requirements. RESULTS: We modeled the workflow of menu-suggestion activity currently adhered to by dietitians in Malaysia. Based on this workflow, a Web-based system was developed. Initial post evaluation among 10 dietitians indicates that they are comfortable with the organization of the modules and information. CONCLUSIONS: The system has the potential of enhancing the quality of services with the provision of standard and healthy menu plans and at the same time increasing outreach, particularly to rural areas. With its potential capability of optimizing the time spent by dietitians to plan suitable menus, more quality time could be spent delivering nutrition education to the patients.

Evaluation Studies as Topic↗

PubMed2026

Applications of artificial intelligence in robot-assisted surgery: a systematic review.

To characterize applications of artificial intelligence (AI) in robot-assisted surgery, summarize technical and clinical performance, and assess the quality of the available evidence. PubMed, Web of Science Core Collection, and Scopus were searched for English-language journal articles published from 1 January 2020 through 31 October 2025. Randomized, observational, model-development, validation, and feasibility studies evaluating AI in robot-assisted surgery or closely related image-guided minimally invasive workflows were eligible. Two reviewers independently performed study selection, data extraction, and risk-of-bias assessment. Owing to heterogeneity in surgical procedures, AI tasks, analytical units, validation strategies, and outcomes, findings were synthesized descriptively without statistical pooling. The review was registered in the International Prospective Register of Systematic Reviews (CRD420251175699). Seventeen studies were included: seven clinical prediction or decision-support studies, eight intraoperative recognition, segmentation, or image-guided studies, and two training or workflow studies. Five prediction studies reported area-under-the-curve values of 0.74-0.95. Technical studies reported F1 or Dice scores of 0.525-0.995 and task-specific accuracies of 0.840-0.998. Two randomized studies suggested benefits for personalized suturing feedback and automated camera control, but neither established improved patient outcomes. Only one study had low overall risk of bias; the remaining studies were at high or unclear risk or raised some concerns. AI applications in robot-assisted surgery show promise for prediction, intraoperative perception, training, and workflow support. Evidence primarily demonstrates technical feasibility rather than established clinical effectiveness. Independent multicenter validation and prospective evaluation of patient, educational, and workflow outcomes are required before widespread implementation.

Robotic Surgical Procedures↗

PubMed2026

AI echo INSIGHT study: A prospective blinded randomized trial of artificial intelligence echocardiogram interpretation.

BACKGROUND: Transthoracic echocardiography (TTE) is the most commonly performed cardiac imaging modality with over 30 million studies annually. Demand for timely expert interpretation continues to outpace capacity, creating diagnostic delays and inter-observer variability that impact patient care. Recent research has suggested computer vision artificial intelligence (AI) models can generate accurate preliminary comprehensive TTE reports, however, prospective evaluation is needed to determine whether AI-assisted TTE interpretation can improve clinician efficiency while preserving diagnostic accuracy. METHODS: AI ECHO INSIGHT is a prospective randomized blinded clinical trial conducted at Kaiser Permanente Northern California that will evaluate 1200 historical TTE studies (1000 consecutive unselected studies plus 200 with moderate or greater valvular disease) interpreted using three workflows: (1) AI-generated preliminary report finalized by a blinded cardiologist (AI-assisted); (2) cardiologist-generated preliminary report finalized by a blinded cardiologist (cardiologist-assisted); and (3) sonographer-generated preliminary report finalized by a blinded cardiologist (sonographer-assisted). The primary outcome is the rate of substantial change between preliminary and final reports, comparing the AI-assisted workflow to the pooled cardiologist-assisted and sonographer-assisted workflows. Secondary outcomes include cardiologist interpretation time for report finalization, superiority testing for diagnostic accuracy, and reporting consistency. CONCLUSION: AI ECHO INSIGHT is a prospective randomized blinded clinical trial evaluating the clinical impact of AI-assisted TTE interpretation on diagnostic accuracy, cardiologist efficiency, and reporting consistency in real-world echocardiography workflows. TRIAL REGISTRATION: ClinicalTrials.gov registration number NCT07229300.

Humans↗

PubMed2026

A hybrid and cost-efficient barcoding strategy for full-length 16S rRNA gene nanopore sequencing of environmental samples.

BACKGROUND: Accurate species-level identification of bacteria in complex environmental samples is essential for applications in biotechnology, ecological monitoring, and clinical diagnostics. Short-read platforms such as Illumina frequently truncate the 16S rRNA gene, limiting taxonomic resolution. In this work, we applied Oxford Nanopore Technology (ONT) long-read sequencing to full-length 16S rRNA amplicon in samples from natural soil amended with lignocellulosic biomass and a simplified microbial community derived from cultures grown on selective and differential carboxymethyl cellulose (CMC)-based substrates, with the aim to evaluate the difference in performance between a real, complex community and a less complex system. To reduce consumable costs, we substituted the standard ONT Barcoding kits with an in-house hybrid barcoding workflow. Specifically, PacBio PCR-based barcoding protocol was used for sample indexing, followed by library preparation using the ONT Ligation Sequencing Kit. This simplified approach retained compatibility with MinION and Flongle flow cells and supported accurate downstream demultiplexing while lowering barcode costs substantially. Additionally, a new bioinformatic workflow tailored to ONT data was implemented. RESULTS: Overall, the hybrid protocol significantly reduced per-sample barcoding costs while preserving high sequencing quality and throughput. The sequencing run yielded over 5 Gb of quality-filtered data (Q-score ≥ 10). Furthermore, the new bioinformatic workflow allowed taxonomic assignment at the species level for 49.38% of annotated taxa, compared to just 4.59% using Illumina NovaSeq sequencing of the V3-V4 region. ONT also recovered 2.3 times more genera and 1.3 times more families. Although 16S rRNA gene sequencing often cannot distinguish between closely related species, particularly within taxonomically complex groups, in this work, full-length reads substantially improved both taxonomic resolution and database matching. CONCLUSIONS: These results show that full-length 16S rRNA sequencing with ONT, paired with a low-cost barcoding strategy, enhanced taxonomic resolution compared to short-read workflows. This approach also offers a scalable and cost-effective option for high-resolution microbiome profiling in research and applied settings.

RNA, Ribosomal, 16S↗

PubMed2005

An Improved Publication Process for the UMVF.

The "Université Médicale Virtuelle Francophone" (UMVF) is a federation of French medical schools. Its main goal is to share the production and use of pedagogic medical resources generated by academic medical teachers. We developed an Open-Source application based upon a workflow system which provides an improved publication process for the UMVF. For teachers, the tool permits easy and efficient upload of new educational resources. For web masters it provides a mechanism to easily locate and validate the resources. For both the teachers and the web masters, the utility provides the control and communication functions that define a workflow system.For all users, students in particular, the application improves the value of the UMVF repository by providing an easy way to find a detailed description of a resource and to check any resource from the UMVF to ascertain its quality and integrity, even if the resource is an old deprecated version. The server tier of the application is used to implement the main workflow functionalities and is deployed on certified UMVF servers using the PHP language, an LDAP directory and an SQL database. The client tier of the application provides both the workflow and the search and check functionalities and is implemented using a Java applet through a W3C compliant web browser. A unique signature for each resource, was needed to provide security functionality and is implemented using the MD5 Digest algorithm. The testing performed by Rennes and Lille verified the functionality and conformity with our specifications.

Education, Medical↗

PubMed2002

Impact of speech recognition on radiologist productivity.

A survey was conducted of radiology practices with productivity data from at least 3 of the following 4 workflows: film with manual transcription, filmless with manual transcription, film with speech recognition, and filmless with speech recognition. Two surveys were submitted to candidate sites. The first was used to ascertain suitable available data for follow-up. The second survey requested data for report turn around times, full-time equivalent (FTE) staffing levels, and report volume. Data were collected and stored in a Microsoft Access database and statistical analysis performed in Excel. Whereas several metrics were used, the normalized figure of reports-per-day/FTE was found to have improved an average of 1.9 (for filmless with speech recognition) and 2.3 (for film with speech recognition) over the film with manual transcription case. Filmless with manual transcription was only 1.4 times the value of the all manual case. At the 10% confidence level, both filmless with manual transcription and film with speech recognition workflows were found to have statistically significant enhanced productivity. Insufficient data exist to show if the fully automated workflow (filmless with speech recognition) offers benefits over 2 previous semiautomated workflows.

Data Collection↗

PubMed2006

Flying blind: using a digital dashboard to navigate a complex PACS environment.

Radiology workflows have become more distributed and complicated, and fewer tangible cues are available to the radiologist to help optimize task prioritization and selection. Additionally, faster scanners, more detailed exams, and increased demand for imaging services have precipitated a potential image overload for today's radiologists who are pressured to provide efficient, quality service in less time. Radiologists are faced with the task of operating within complex systems but are lacking tools to efficiently and effectively monitor these systems in real time. Dashboard technology can help address this deficiency in radiology and facilitate informed, optimized decisions about workflow. Possible areas of application include workflow consolidation, workload distribution, and urgency evaluation. Dashboards should be optimized, context-sensitive, customizable, and workflow-integrated. Further research is needed to identify the most important dashboard metrics, determine their optimal display, and validate their utility.

Data Display↗

PubMed2005

The anatomy of decision support during inpatient care provider order entry (CPOE): empirical observations from a decade of CPOE experience at Vanderbilt.

The authors describe a pragmatic approach to the introduction of clinical decision support at the point of care, based on a decade of experience in developing and evolving Vanderbilt's inpatient "WizOrder" care provider order entry (CPOE) system. The inpatient care setting provides a unique opportunity to interject CPOE-based decision support features that restructure clinical workflows, deliver focused relevant educational materials, and influence how care is delivered to patients. From their empirical observations, the authors have developed a generic model for decision support within inpatient CPOE systems. They believe that the model's utility extends beyond Vanderbilt, because it is based on characteristics of end-user workflows and on decision support considerations that are common to a variety of inpatient settings and CPOE systems. The specific approach to implementing a given clinical decision support feature within a CPOE system should involve evaluation along three axes: what type of intervention to create (for which the authors describe 4 general categories); when to introduce the intervention into the user's workflow (for which the authors present 7 categories), and how disruptive, during use of the system, the intervention might be to end-users' workflows (for which the authors describe 6 categories). Framing decision support in this manner may help both developers and clinical end-users plan future alterations to their systems when needs for new decision support features arise.

Admitting Department, Hospital↗

PubMed2026

Clinical accuracy and short-term outcomes of intraoral photogrammetry for complete-arch implant rehabilitation: A retrospective multicentre study on 35 patients.

OBJECTIVES: To evaluate the clinical accuracy and short-term outcomes of complete-arch implant-supported fixed dental prostheses (ISFDPs) fabricated using an intraoral photogrammetry (IPG) based digital workflow in completely edentulous patients. METHODS: This multicenter retrospective clinical study included 35 patients rehabilitated with 52 complete-arch ISFDPs (10 FP1, 18 FP2 and 24 FP3 restorations) supported by 221 implants. All definitive prostheses were designed and fabricated using a fully digital workflow initiated by IPG acquisition with the Aoralscan Elite IPG® (SHINING 3D). The primary outcome was clinical accuracy, assessed at definitive prosthesis delivery through evaluation of passive fit using the Sheffield test and radiographic verification. Secondary outcomes included biologic and prosthetic complications, as well as implant and prosthesis survival rates during the follow-up. RESULTS: Passive fit was achieved in all definitive restorations (100%). Radiographic evaluation confirmed accurate marginal adaptation at the implant-prosthesis interface in all cases. No statistically significant differences in clinical accuracy were observed according to treated arch, number of supporting implants, or prosthetic design (P > .05). During a mean follow-up period of 12.1 ± 3.5 months, biologic and prosthetic complications were limited and generally minor. Implant survival was 99.5%, and prosthesis survival was 100%. CONCLUSIONS: Within the limitations of this retrospective clinical study, the IPG based workflow demonstrated high clinical accuracy and predictable short-term outcomes for complete-arch implant rehabilitation, consistently enabling passive fit and favorable prosthetic performance. CLINICAL RELEVANCE: IPG may represent a clinically reliable and predictable approach for complete-arch digital implant impression acquisition. The high rates of passive fit, together with the low incidence of biologic and prosthetic complications observed in this multicenter clinical study, support the use of IPG based workflows for the fabrication of complete-arch ISFDPs.

Humans↗

PubMed2026

Rapid CRISPR-based bovine embryo sexing to streamline genotype-informed cattle breeding.

Cattle in vitro fertilisation and embryo transfer programmes increasingly rely on embryo-level selection to accelerate genetic gain, but current sexing and genotyping workflows can be costly, slow and logistically demanding. This study developed an efficient, low-resource workflow for bovine embryo sexing that combines whole genome amplification (WGA) with recombinase polymerase amplification-CRISPR-Cas12a (RPA-Cas12a). It also assessed whether the same WGA biopsy products could be used for downstream single nucleotide polymorphism (SNP) microarray genotyping. A one-tube RPA-Cas12a assay targeting the bovine Y-chromosome S4 repeat was developed for fluorescence and lateral flow assay (LFA) readouts. Analytical sensitivity was assessed using serially diluted bovine genomic DNA (gDNA), and breed robustness was tested using male and female gDNA from five major beef breeds and Holstein cattle. The workflow was then applied to WGA products from 22 bovine blastocyst biopsies, with sex calls validated against an established real-time PCR melt curve assay and 100K SNP microarray genotyping. The assay detected male bovine gDNA down to 100 pg using both fluorescence and LFA readouts, with no signal from female gDNA. Male-specific detection was consistent across all breeds tested. All WGA-RPA-Cas12a sex calls from blastocyst biopsies were concordant with real-time PCR and SNP microarray sex calls, and WGA biopsy products produced genome-wide SNP call rates above 85%. This workflow provides a practical approach for rapid bovine embryo sex triage and could reduce unnecessary cryopreservation and genotyping while improving the efficiency of genotype-informed cattle breeding programmes.

Bovine embryo↗

PubMed2026

Liquid biopsy-based detection of circulating and exfoliated cholangiocarcinoma tumor cells from blood and bile using heparan sulfate octasaccharides on integrated microfluidic systems.

Early diagnosis of cholangiocarcinoma (CCA) remains challenging because existing diagnostic approaches often lack sufficient sensitivity for reliable detection of early-stage disease. Circulating tumor cells (CTCs) in blood and exfoliated tumor cells (ETCs) in bile represent valuable targets for liquid biopsy-based detection; however, their low abundance and the complexity of clinical sample analysis pose substantial technical challenges for reliable enrichment and identification. Herein, we present a reproducible workflow for isolating and identifying CCA tumor cells from blood for CTCs and bile for ETCs using synthetic cell-surface heparan sulfate (HS) octasaccharide-functionalized magnetic beads (MBs) on integrated microfluidic systems. The method combined sample pre-processing, magnetic bead-based enrichment, controlled low-shear mixing and immunofluorescence-based identification into a unified workflow compatible with distinct clinical sample types. Key operational parameters, including MB concentration, mixing frequency, and pressure settings, were detailed to facilitate consistent performance. Using this workflow, tumor cell capture rates of approximately 70% in bile (for ETCs) and blood (for CTCs) were achieved, with a total processing time of 60-90 min per sample under clinically relevant low-abundance conditions. The platform enables reliable detection of as few as 1 tumor cell per mL of blood or bile. This method provides a practical and adaptable strategy for glycosaminoglycan-mediated liquid biopsy applications and may be extended to other tumor-cell enrichment workflows involving heterogeneous cell-surface interactions.

Humans↗

PubMed2026

Evaluation and Optimization of Different Digestion Strategies for In-Depth Proteomic Characterization of Residual Host Cell Proteins in rAAV-Based Gene Therapy Products.

Recombinant adeno-associated virus vectors (rAAVs) are the most important vectors for in vivo gene therapies, yet their safety relies on low levels of residual host cell proteins (HCPs). While mass spectrometry-based proteomics enables sensitive and untargeted HCP profiling, it faces challenges with matrix interferences from purification buffers and the high dynamic range between abundant viral capsids and trace HCPs. Although sample preparation methods that address these challenges are well-established for antibody products, their adaptation to rAAV purification stages and products remains largely unexplored. In this study, we systematically evaluated three widely used proteomic sample preparation workflows─In-Solution, FASP, and SP3─across different stages of rAAV purification. In addition, each workflow was tested under both standard denatured digestion conditions and a "native" digestion strategy designed to reduce dynamic range by preserving capsid integrity while selectively digesting HCPs. This comparison identified the native FASP protocol as the most effective sample preparation method for overcoming matrix interference and dynamic range challenges, consistently outperforming other workflows in HCP identification across purification stages. Further optimization of the native FASP workflow enhanced its performance, achieving the highest host cell (HC) proteome depth, particularly in highly purified drug substance samples. This optimized sample preparation strategy provides a robust and easy-to-use framework for deep characterization of the host cell proteome in rAAV samples. By enabling deeper insights into the HCP profile, this approach supports improved understanding of the rAAV purification process and facilitates the development of targeted strategies to enhance product quality and safety.

Dependovirus↗

PubMed2026

Selective Enrichment of Newly Synthesized Proteins Using Phos-Tag Click Tip Enables Nascent Proteome Analysis in Influenza A Virus Infection.

Profiling of newly synthesized proteins (NSPs) provides access to dynamic changes in protein production that accompany acute cellular responses. Bioorthogonal noncanonical amino acid tagging (BONCAT)-based approaches enable selective labeling of NSPs; however, their broader application remains constrained by labor-intensive enrichment workflows and limited sensitivity for direct peptide-level analysis. Here, we developed a workflow termed "Phos-tag Click Tip" by integrating a phosphorylated variant of bicyclononyne (pBCN) with Phos-tag affinity purification to selectively capture azidohomoalanine (AHA)-labeled peptides for newly synthesized proteome analysis (NSProteomics). This approach overcomes key limitations of conventional proteomics and BONCAT-based strategies by enabling efficient enrichment and sensitive detection of NSP-derived peptides. Using this workflow, we performed comprehensive NSP profiling of host cells during influenza A virus infection. We identified dynamic changes in distinct NSP profiles associated with viral replication, host restriction, and immune responses, many of which were not readily detected with conventional whole-cell- or phospho-proteomic analyses. Overall, the Phos-tag Click Tip workflow provides a complementary approach for stimulus-responsive NSP profiling, offering functionally relevant insights into host-virus interactions and cellular response mechanisms.

Proteome↗

PubMed2026

StrainMake: reproducible hybrid metagenomics with MAG recovery and strain-level resolution.

SUMMARY: Metagenomic workflows involve complex multi-step analyses, from quality control and assembly to binning, annotation, and strain-level profiling. Few existing metagenomic pipelines achieve the combination of flexibility, reproducibility, and hybrid assembly support within a unified workflow. We present StrainMake, a Snakemake-based workflow for de novo metagenomic analysis from short, long, or hybrid sequencing data. StrainMake integrates widely used tools across all major steps-quality control, assembly, binning, dereplication, taxonomic and functional annotation-while also providing non-redundant gene catalogues, community-scale metabolic models, and strain-level microdiversity metrics. The modular design enables the use of alternative tools, scalable execution on HPC systems, and full reproducibility through Snakemake and Conda. RESULTS: Applied to the CAMI II strain-madness dataset, StrainMake produced high-quality assemblies and metagenome-assembled genomes (MAGs), while enabling strain-resolved comparisons across samples. Hybrid assemblies improved contiguity, whereas short-read assemblies offered faster runtimes, illustrating the workflow's benchmarking capacity. AVAILABILITY AND IMPLEMENTATION: StrainMake is open source and available at https://github.com/UMMISCO/strainmake, together with comprehensive documentation. Generated data are deposited in Zenodo (doi: 10.5281/zenodo.16950162).

Metagenomics↗

PubMed2006

XQTav: an XQuery processor for Taverna environment.

UNLABELLED: Taverna workbench is an environment for construction, visualization and execution of bioinformatic workflows that integrate specialized tools available through the internet. It is gaining popularity fast, because of supporting the most important bioinformatic services and its simple, yet robust graphical notation. Here we present XQTav-an extension of Taverna that provides full integration with XQuery (the query language for XML) engine. XQTav allows execution of XQuery scripts in Taverna workflow diagrams. All existing Taverna processors can be accessed in the XQuery scripts. This provides an alternative way of specifying subworkflows in Taverna and is useful when one deals with query-like algorithms (e.g. filters and inner joins). Moreover, XQtav may be used to automatically generate an XQuery script that is equivalent to Taverna's workflow. This constitutes another way of creating and enacting bioinformatic workflows: overall structure of a diagram is drawn in Taverna environment, XQuery code is generated and possibly adjusted by hand. It can be executed by XQuery engines or incorporated into other software environments. AVAILABILITY: XQtav is an open source software. It may be downloaded from http://xqtav.sourceforge.net/. The page also contains various tutorials and examples, including the one described in this report.

Algorithms↗

PubMed2026

Genetic testing and reporting: What the endocrinologists should know and can expect (Joint position paper of the ENDO-ERN).

Over the last decade, next generation sequencing (NGS) has become an essential tool for diagnostic DNA testing in human genetics. To improve the understanding of available genetic testing strategies and to facilitate the request of genetic testing in daily endocrine practice, clinical and laboratory experts in the field have summarized the major issues which should be known and considered. In this joint position paper of the ENDO-ERN, the roles and responsibilities of the health care professionals involved in the diagnostic workflow are described, and the major issues concerning genetic testing workflows are overviewed. These issues encompass all relevant steps, including test request and pre-analytical procedures, laboratory and data processing workflows, quality assurance, and reporting. As NGS procedures result in an increasing number of variants of unknown significance and incidental findings, these aspects are addressed as well. Accompanied by illustrations of the genetic diagnostic workflow and of concise reports for a fast orientation about the major aspects of genetic testing, this joint paper should support the health care professionals during a request for genetic testing.

VUS↗