Interactive Table Research Articles

PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization.

Single-cell perturbation (scPerturbation) sequencing techniques, represented by single-cell genetic perturbation (e.g. Perturb-seq) and single-cell chemical perturbation (e.g. sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative sequencing techniques empower researchers to dissect perturbation effects in biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists in the availability of a dedicated database for exploring scPerturbation data. To address this gap, we present PerturBase, the most comprehensive database designed for the analysis and visualization of scPerturbation data (http://www.perturbase.cn/). PerturBase curates 122 datasets from 46 publicly available studies, covering 115 single-modal and 7 multi-modal datasets that include 24254 genetic and 230 chemical perturbations from approximately 5 million cells. The database, comprising the 'Dataset' and 'Perturbation' modules, provides insights into various results, encompassing quality control, denoising, differential gene expression analysis, functional analysis of perturbation effectsand characterization of relationships between perturbations. All the datasets and results are presented on user-friendly, easy-to-browse web pages and can be visualized through intuitive and interactive plot and table formats. In summary, PerturBase stands as a pioneering, high-content database intended for searching, visualizingand analyzing scPerturbation datasets, contributing to a deeper understanding of perturbation effects.

Meeting report from the 3rd ISCBH-ERN BOND Achondroplasia Workshop on Long Bone Pathology in Children with Achondroplasia, Salzburg, Austria 22nd June 2024

A pre-meeting workshop on Long Bone Pathology in Children with Achondroplasia was held in Salzburg, Austria at the 11th International Conference on Children's Bone Health (ICCBH) 22–25 June 2024. There remains poor understanding and awareness amongst physicians managing achondroplasia of the underlying pathophysiology, radiology, natural history and orthopaedic procedures available for long bone deformities and restrictions. The structure of the workshop consisted of presentation of the results of a multinational patient survey on views of leg lengthening in achondroplasia, lectures, a debate and an interactive round table discussion. In total 150 attendees from 71 different cities and 31 countries were in attendance.

Interactive Table Synthesis With Natural Language.

Tables are a ubiquitous data format for insight communication. However, transforming data into consumable tabular views remains a challenging and time-consuming task. To lower the barrier of such a task, research efforts have been devoted to developing interactive approaches for data transformation, but many approaches still presume that their users have considerable knowledge of various data transformation concepts and functions. In this study, we leverage natural language (NL) as the primary interaction modality to improve the accessibility of average users to performing complex data transformation and facilitate intuitive table generation and editing. Designing an NL-driven data transformation approach introduces two challenges: 1) NL-driven synthesis of interpretable pipelines and 2) incremental refinement of synthesized tables. To address these challenges, we present NL2Rigel, an interactive tool that assists users in synthesizing and improving tables from semi-structured text with NL instructions. Based on a large language model and prompting techniques, NL2Rigel can interpret the given NL instructions into a table synthesis pipeline corresponding to Rigel specifications, a declarative language for tabular data transformation. An intuitive interface is designed to visualize the synthesis pipeline and the generated tables, helping users understand the transformation process and refine the results efficiently with targeted NL instructions. The comprehensiveness of NL2Rigel is demonstrated with an example gallery, and we further confirmed NL2Rigel's usability with a comparative user study by showing that the task completion time with NL2Rigel is significantly shorter than that with the original version of Rigel with comparable completion rates.

ShinySperm: navigating the sperm proteome landscape.

Context Integrated omics studies hold a crucial role in improving our understanding of reproductive biology. However, the complex datasets so generated are often only accessible via supplementary data files, which lack the capacity for interactive features to allow users to readily interrogate and visualise data of interest. Aims The intent of this technical note was to develop an interactive web-based application that enables detailed interrogation of a representative sperm proteome, facilitating a deeper understanding of the proteins identified, their relative abundance, classifications, functions, and associated phenotypes. Methods We developed a Shiny web application, ShinySperm (https://reproproteomics.shinyapps.io/ShinySperm/ ), utilising R and several complementary libraries for data manipulation (dplyr), interactive tables (DT), and visualisation (ggplot2, plotly). ShinySperm features a responsive user interface, dynamic filtering options, interactive charts, and data export capabilities. Key results ShinySperm allows users to interactively search, filter, and visualise sperm proteomics data based on key features (e.g. protein classification, sperm cell domain, presence, or absence at different maturation stages). This application responds live to filtering options and enables the generation of interactive plots and tables, thus enhancing user engagement and understanding of the data. Conclusions ShinySperm provides a robust platform for the dynamic exploration of epididymal sperm proteome data. It significantly improves accessibility and interpretability of complex datasets, allowing for effective data-driven insights. Implications This technical note highlights the potential of interactive web applications in reproductive biology and provides a plug and play script for the field to produce applications for meaningful researcher interaction with complex omic datasets.

МУЗИКАТА В СВЕТА НА ДЕТЕТО

This publication describes an innovative pedagogical practice in the educational subject ‘Music’ on the topic ‘Spring and music’. The musical activities in it are aimed to improve children’s performance skills in five-year-old children in singing, playing with children’s musical instruments, motor reflection of music, as well as strengthening their ideas about the types of musical instruments in terms of appearance and way of sound extraction. Open pedagogical practice is part of the activities of the National Program ‘It’s good in kindergarten’. The use of modern digital educational tools such as an interactive board, an interactive fl oor, interactive tables, as well as web-based tools – contribute to the successful formation of children’s performance skills in singing, playing with children’s musical instruments and moving with music. Applying the approaches ‘learning by playing’, ‘learning by doing’ and ‘learning by experiencing’ enriched musical competence, emotional responsiveness and a positive evaluative attitude towards their own skills and the skills of others.

Racial and ethnic disparities in reproductive medicine in the United States: a narrative review of contemporary high-quality evidence

There has been increasing debate around how or if race and ethnicity should be used in medical research-including the conceptualization of race as a biological entity, a social construct, or a proxy for racism. The objectives of this narrative review are to identify and synthesize reported racial and ethnic inequalities in obstetrics and gynecology (ob/gyn) and develop informed recommendations for racial and ethnic inequity research in ob/gyn. A reproducible search of the eight highest impact ob/gyn journals was conducted. Articles published between January 1, 2010, and June 30, 2023 containing keywords related to racial and ethnic disparities, bias, prejudice, inequalities, and inequities were included (n=318). Data were abstracted and summarized into four themes: 1) access to care, 2) adherence to national guidelines, 3) clinical outcomes, and 4) clinical trial diversity. Research related to each theme was organized topically under the headings i) obstetrics, ii) reproductive medicine, iii) gynecologic cancer, and iv) other. Additionally, interactive tables were developed. These include data on study timeline, population, location, and results for every article. The tables enable readers to filter by journal, publication year, race and ethnicity, and topic. Numerous studies identified adverse reproductive outcomes among racial and ethnic minorities as compared to white patients, that persist despite adjusting for differential access to care, socioeconomic or lifestyle factors, and clinical characteristics. These include higher maternal morbidity and mortality among Black and Hispanic/Latinx patients; reduced success during fertility treatments for Black, Hispanic/Latinx, and Asian patients; and lower survival rates and lower likelihood of receiving guideline concordant care for gynecological cancers for non-white patients. We conclude that many racial and ethnic inequities in ob/gyn cannot be fully attributed to patient characteristics or access to care. Research focused on explaining these disparities based on biological differences incorrectly reinforces the notion of race as a biological trait. More research that deconstructs race and assesses efficacy of interventions to reduce these disparities is needed.

Tracking the FDA precision oncology drug approval landscape in OncoKB.

e13507 Background: OncoKB ( www.oncokb.org ), Memorial Sloan Kettering's (MSK) precision oncology knowledge base, is a comprehensive database that provides curated information about the oncogenic effect and clinical implications of genomic alterations in cancer. OncoKB assigns evidence-based levels of clinical actionability to individual mutational events in a tumor type-specific context and is the first somatic variant database to be partially recognized by the US-FDA. As of February 2024, OncoKB contains annotations for >7600 alterations in >840 cancer-associated genes, including 59 level-1 or 2 genes (standard care, specified in the FDA-drug label or professional guidelines), 8 level-3A and 12 level-4 genes (predictive of drug response based on well-powered clinical studies or compelling biological evidence respectively). As the field of precision oncology continues to evolve with the identification of new molecular targets and development of novel drug/drug combinations, we sought to provide OncoKB users with a resource that quantitates the landscape of FDA-approved precision oncology therapies in real-time. Methods: To provide clinicians with an easily accessible and transparent list of FDA-approved drugs that require molecular biomarker testing to determine patient eligibility for use of the drug, we curated and categorized all FDA-approved oncology drugs from the FDA’s Oncology / Hematologic Malignancies Approval Notifications webpage from 1998 to present. For each drug we recorded its mechanism of action and whether it qualifies as a targeted therapy (a cancer drug that binds to or inhibits a specific protein target) or a precision oncology therapy (a drug that is most effective in a molecularly defined subset of patients and for which pre-treatment molecular profiling is required for optimal patient selection). For all precision oncology therapies we further listed the FDA-recognized biomarker(s) from the FDA-drug label and determined whether a DNA-based method could be used for biomarker detection. The data are publicly available via an interactive and downloadable table on OncoKB’s Oncology Therapies page , which is updated on a bi-monthly basis. Results: Between June 1998 and January 2024, 217 novel oncology drugs were FDA-approved, 83.4% (n=181) of which were classified as targeted therapies. Greater than half (51.9%, n=94) of targeted therapies were classified as precision oncology therapies. Currently, 52 genes as well as MSI-H and TMB-H status are FDA-recognized biomarkers of treatment response. Over the past five years, 75 novel oncology drugs were FDA-approved, 46 (61.3%) of which were precision oncology therapies. Conclusions: OncoKB’s publicly available Oncology Therapies page provides insight into the pace of growth of the precision oncology drug landscape and serves as a complementary tool for clinicians who utilize OncoKB to determine whether a patient with cancer should receive biomarker testing.

Disparities in clinical trial participation: Survey of patients with cancer at an academic medical center.

e13720 Background: This study aims to understand cancer patients' attitudes toward clinical trials and identify barriers to participation, because low participation, especially among minorities, perpetuates poor outcomes and disparities. Methods: A survey was conducted at the University of Cincinnati Cancer Center (UCCC) to assess patients' experiences and attitudes toward clinical trials, previous trial participation, and future trial interest. The pen-and-paper survey, administered by a coordinator (KM), took 5-10 minutes. Frequency tables and Chi-square tests in SAS summarized the findings. Results: From April to August 2023, a survey was offered to solid tumor patients at UCCC during their clinic visits. Participation was voluntary; 300 patients completed the survey. The cohort had 56% females and 77% Whites, with equal educational levels up to (51%) and beyond high school (49%), but with notable racial differences (Table). Index cancer diagnoses were lung (15%), head/neck (11%), breast (10%), colorectal (8%), pancreatic (8%), ovarian (6%), prostate (6%), gastroesophageal (6%), endometrial (5%), and various others (25%). Of 300 participants, only 32% had ever been asked to participate in a clinical trial; more Whites vs non-Whites; 84% chose to participate, with notable differences by race (Table). These differences were not attributable to education or sex. Of the 81 patients who chose to participate, 96% participated to gain access to new treatments, and 75% participated to contribute to research; only 11% did it for financial incentives. There were also differences by race among the 15 who declined participation (Table). Of the 203 who had never been asked to participate in a trial, 71% indicated that they would be willing to participate in the future, but with a strong sex:race interaction (Table). Nearly all (99%) indicated that they would participate to have access to new treatments; many (57%) wanted to contribute to research. Conclusions: This survey shows that many solid tumor patients are not offered clinical trials, and reveals racial disparities in patient willingness, especially among non-White men. Promisingly, there's a notable readiness among patients to join trials for treatment access and research. Efforts should focus on improving clinical trial portfolios, enhanced outreach, and target population education and trust-building. [Table: see text]

Web-based Dashboard on ECMO Utilization in Germany: An Interactive Visualization, Analyses, and Prediction Based on Real-life Data

In Germany, a comprehensive reimbursement policy for extracorporeal membrane oxygenation (ECMO) results in the highest per capita use worldwide, although benefits remain controversial. Public ECMO data is unstructured and poorly accessible to healthcare professionals, researchers, and policymakers. In addition, there are no uniform policies for ECMO allocation which confronts medical personnel with ethical considerations during health crises such as respiratory virus outbreaks.Retrospective information on adult and pediatric ECMO support performed in German hospitals was extracted from publicly available reimbursement data and hospital quality reports and processed to create the web-based ECMO Dashboard built on Open-Source software. Patient-level and hospital-level data were merged resulting in a solid base for ECMO use analysis and ECMO demand forecasting with high spatial granularity at the level of 413 county and city districts in Germany.The ECMO Dashboard (https://www.ecmo-dash.de/), an innovative visual platform, presents the retrospective utilization patterns of ECMO support in Germany. It features interactive maps, comprehensive charts, and tables, providing insights at the hospital, district, and national levels. This tool also highlights the high prevalence of ECMO support in Germany and emphasizes districts with ECMO surplus – where patients from other regions are treated, or deficit – origins from which ECMO patients are transferred to other regions. The dashboard will evolve iteratively to provide stakeholders with vital information for informed and transparent resource allocation and decision-making.Accessible public routine data could support evidence-informed, forward-looking resource management policies, which are urgently needed to increase the quality and prepare the critical care infrastructure for future pandemics.

YOUTUBE COMMENTS SCRAPING AND SENTIMENT ANALYSIS

The Social Media Sentiment Analysis web application is a powerful tool designed for content creators on various social media platforms, including YouTube. This application provides an intuitive interface for extracting and analyzing comments from YouTube videos, enabling content creators to gain valuable insights into the sentiment expressed by their viewers. By entering the YouTube video URL and an email address, users can harness the capabilities of this application to gain a comprehensive understanding of how their audience perceives their content. Leveraging the YouTube Data API, the application efficiently retrieves comments from the specified video. The application generates three files: comprehensive comments, positive comments, and negative comments, which are sent via email as Excel files. An interactive HTML table showcases sentiment distribution. This user-friendly application empowers content creators to track and enhance audience engagement on social media platforms, such as YouTube, through data-driven decision-making. Key Words: Social Media Sentimet Analysis , web application ,Youtube , analyzing comments , sentiment expressed , positive comments , negative comments

Updates to the Alliance of Genome Resources central infrastructure.

The Alliance of Genome Resources (Alliance) is an extensible coalition of knowledgebases focused on the genetics and genomics of intensively studied model organisms. The Alliance is organized as individual knowledge centers with strong connections to their research communities and a centralized software infrastructure, discussed here. Model organisms currently represented in the Alliance are budding yeast, Caenorhabditis elegans, Drosophila, zebrafish, frog, laboratory mouse, laboratory rat, and the Gene Ontology Consortium. The project is in a rapid development phase to harmonize knowledge, store it, analyze it, and present it to the community through a web portal, direct downloads, and application programming interfaces (APIs). Here, we focus on developments over the last 2 years. Specifically, we added and enhanced tools for browsing the genome (JBrowse), downloading sequences, mining complex data (AllianceMine), visualizing pathways, full-text searching of the literature (Textpresso), and sequence similarity searching (SequenceServer). We enhanced existing interactive data tables and added an interactive table of paralogs to complement our representation of orthology. To support individual model organism communities, we implemented species-specific "landing pages" and will add disease-specific portals soon; in addition, we support a common community forum implemented in Discourse software. We describe our progress toward a central persistent database to support curation, the data modeling that underpins harmonization, and progress toward a state-of-the-art literature curation system with integrated artificial intelligence and machine learning (AI/ML).

An improved time advance method for distributed multi-resolution modelling with interactive deviation characterization

Multi-resolution modelling (MRM) has been increasingly applied in engineering practice. While in a distributed simulation environments, time advance method for MRM is less studied. When the system is running in a relatively low-resolution status, it usually adopts basic time advance modes to save simulation resources. However, these basic modes usually suffer from inaccurate response of interactions and are separate from the resolution switching process. In this paper, we propose an improved time advance method for distributed multi-resolution models. We introduce an interaction table to enable dynamic management of interactions, and decouple the interaction request process from the interaction response process, resulting in a more fine-grained interactive mode. Moreover, the interactive deviation index is introduced to quantitatively characterize the cumulative errors from delayed interactions. This index has been incorporated into resolution switching conditions to provide a more flexible and intuitive way for multi-resolution modelling. Proposed method has been verified on both theoretical cases and practical applications, and can achieve high simulation accuracy with less time consumption.

A Decision Aid to Support Tubal Sterilization Decision-Making Among Pregnant Women

Tubal sterilization is common, especially among individuals with low income. There is substantial misunderstanding about sterilization among those who have undergone the procedure, suggesting suboptimal decision-making about a method that permanently ends reproductive capacity. To test the efficacy of a web-based decision aid for improving tubal sterilization decision quality. This randomized clinical trial conducted between March 2020 and November 2023 included English- or Spanish-speaking pregnant cisgender women aged 21 to 45 years who had Medicaid insurance and were contemplating tubal sterilization after delivery. Participants were recruited from outpatient obstetric clinics in 3 US cities. Participants were randomized 1:1 to usual care (control arm) or to usual care plus a web-based decision aid (MyDecision/MiDecisión) (intervention arm). The aid includes written, audio, and video information about tubal sterilization procedures; an interactive table comparing contraceptive options; values-clarifying exercises; knowledge checks; and a summary report. The co-primary outcomes were tubal sterilization knowledge and decisional conflict regarding the contraceptive decision. Knowledge was measured as the percentage of correct responses to 10 true-false items. Decisional conflict was measured using the low-literacy Decision Conflict Scale, with lower scores on a range from 0 to 100 indicating less conflict. Among the 350 participants, mean (SD) age was 29.7 (5.1) years. Compared with the usual care group, participants randomized to the decision aid had significantly higher tubal sterilization knowledge (mean [SD] proportion of questions answered correctly, 76.5% [16.9%] vs 55.6% [22.6%]; P < .001) and lower decisional conflict scores (mean [SD], 12.7 [16.6] vs 18.7 [20.8] points; P = .002). The greatest knowledge differences between the 2 groups were for items about permanence, with more participants in the intervention arm answering correctly that tubal sterilization is not easily reversible (90.1% vs 39.3%; odds ratio [OR], 14.2 [95% CI, 7.9-25.4]; P < .001) and that the tubes do not spontaneously "come untied" (86.6% vs 33.7%; OR, 13.0 [95% CI, 7.6-22.4]; P < .001). MyDecision/MiDecisión significantly improved tubal sterilization decision-making quality compared with usual care only. This scalable decision aid can be implemented into clinical practice to supplement practitioner counseling. These results are particularly important given the recent increase in demand for permanent contraception after the US Supreme Court decision overturning federal abortion protections. ClinicalTrials.gov Identifier: NCT04097717.

Pengaruh Perendaman Zat Pengatur Tumbuh Giberelin (GA3) pada Perkecambahan Benih Kopi Arabika (Coffea arabica L.) Varietas S795

Coffee is one of the plantation commodities that has an important role in the national economy, especially as a source of foreign exchange because it has high economic value. The productivity of arabica coffee (Coffea arabica L.) in Indonesia in the 2019/2020 period decreased by 2.7% with a total production of around 95 million sacks. This study aims to determine the effect of gibberellin (GA3) on the germination of the arabica coffee bean variety S795. The experimental design was a completely randomized design factorial consisting of two factors with four replications for each treatment. The first factor was the plant growth regulator gibberellin concentration which consisted of 100 ppm (K1), 200 ppm (K2), and 300 ppm (K3). The second factor is the soaking time which consists of 12 hours (P1) and 24 hours (P2). The result showed that the interaction between GA3 concentration and soaking time had no significant effect on all observed parameters (germination percentage, germination rate, seedling height) in the germination of arabica coffee bean variety S795. Based on the table of average interactions between GA3 concentration and soaking time, it can be concluded that the K1P1 treatment with 12 hours of soaking time at a concentration of 100 ppm was the best treatment for the parameters of germination percentage, seedling height, and root length. The K2P1 treatment with 12 hours of immersion time at a concentration of 200 ppm was the best treatment for the germination rate parameter, namely 36.34 days.

Interdisciplinary educational and methodological support of medical and biological disciplines using the resources of the Technopark of Universal Pedagogical Competencies

Introduction. Changes in the higher pedagogical education system require qualitatively new scientific and methodological support for educational programs and improved methodological support for various forms of students' educational work. In the context of modernization of education, modeling the educational process is to be based on an interdisciplinary approach. Technology parks for universal pedagogical competencies significantly expand the capabilities of teaching methods and provide the opportunity to strengthen the practical interdisciplinary training of the future teacher. Changed learning objectives and means of organizing the educational process require new-generation educational and methodological support where interdisciplinary educational and methodological complexes play the leading role, which allows implementing the conceptual approaches of the Federal State Educational Standard of higher education. Materials and methods. The study employed the following methods: theoretical analysis of publications on interdisciplinary educational and methodological support for biomedical disciplines, including identification of the main methodological approaches and principles, basic provisions and components of the integrative approach within such disciplines; a survey of students for assessing the effective implementation of the developed interdisciplinary educational and methodological support and student satisfaction with the quality of teaching biomedical disciplines. 56 undergraduate students (2-5th year) of South Ural State Humanitarian and Pedagogical University (Russian Federation) took part in the survey. Results. The subject of this study is the methodology for forming and developing students’ professional competence using the integrative approach and the resource base of the Technopark of Universal Pedagogical Competencies when studying biomedical disciplines. A means of implementing interdisciplinary learning is interdisciplinary tasks and assignments, including those performed using Technopark equipment (digital neurotechnology laboratory BiTronics Lab, interactive anatomical table Pirogov, binocular digital microscopes with the possibility of video and photo recording of the studied objects. The student survey showed that 85.7% of respondents consider it necessary to use a wider interdisciplinary approach in studying biomedical disciplines to improve the quality of education. Conclusion. Interdisciplinary educational and methodological support of medical and biological disciplines in training biology teachers using the capabilities of the Technopark of Universal Pedagogical Competencies and the pedagogical Quantorium of South Ural State Humanitarian Pedagogical University allows students to develop natural science literacy and provides professional training for a future biology teacher in accordance with the needs of society in the context of modernizing higher pedagogical education.

A Drug Safety Briefing (II) in Transplantation from Real-World Individual Pharmacotherapy Management to Prevent Patient and Graft from Polypharmacy Risks at the Very Earliest Stage.

For early and long-term patient and graft survival, drug therapy in solid organ and hematopoietic stem cell transplantation inevitably involves polypharmacy in patients with widely varying and even abruptly changing conditions. In this second part, relevant medication briefing is provided, in addition to the scores defined in the previously published first part on the design of the Individual Pharmacotherapy Management (IPM). The focus is on the growing spectrum of contemporary polypharmacy in transplant patients, including early and long-term follow-up medications. 1. Unlike the available drug-drug interaction (DDI) tables, for the first time, this methodological all-in-one device refers to the entire risks, including contraindications, special warnings, adverse drug reactions (ADRs), and DDIs. The selection of 65 common critical drugs results from 10 years of daily IPM with real-world evidence from more than 60,800 IPM inpatient and outpatient medication analyses. It includes immunosuppressants and typical critical antimicrobials, analgesics, antihypertensives, oral anticoagulants, antiarrhythmics, antilipids, antidepressants, antipsychotics, antipropulsives, antiemetics, propulsives, proton pump inhibitors (PPIs), sedatives, antineoplastics, and protein kinase inhibitors. As a guide for the attending physician, the drug-related risks are presented in an alphabetical overview based on the Summaries of Product Characteristics (SmPCs) and the literature. 2. Further briefing refers to own proven clinical measures to manage unavoidable drug-related high-risk situations. Drug-induced injuries to the vulnerable graft and the immunosuppressed comorbid patient require such standardized, intensive IPM and the comprehensive preventive briefing toolset to optimize the outcomes in the polypharmacy setting.

Deep learning for survival analysis: a review

The influx of deep learning (DL) techniques into the field of survival analysis in recent years has led to substantial methodological progress; for instance, learning from unstructured or high-dimensional data such as images, text or omics data. In this work, we conduct a comprehensive systematic review of DL-based methods for time-to-event analysis, characterizing them according to both survival- and DL-related attributes. In summary, the reviewed methods often address only a small subset of tasks relevant to time-to-event data—e.g., single-risk right-censored data—and neglect to incorporate more complex settings. Our findings are summarized in an editable, open-source, interactive table: https://survival-org.github.io/DL4Survival. As this research area is advancing rapidly, we encourage community contribution in order to keep this database up to date.

WarenstromInfo: a tool for the easy extraction and visualisation of trade flow data

Epidemiological outbreak investigations often prove to be lengthy and inconclusive due to the time-consuming nature of the currently-used approaches. An alternative approach to address these challenges could involve the application of algorithms to support authorities and food business operators by providing timely, relevant and reliable information. Algorithms, such as gravity models, could be applied as commodity trade models, but they require a large amount of reliable and consistent data on trade for generating projections at international, national or even regional level. Several trade databases, such as UN COMTRADE, EUROSTAT, BACI, CHELEM and GTAP, provide information on trace, albeit with variations in the provided information and in the structure. However, it is worth noting that not all of these databases are freely accessible and data management can pose challenges, hampering the access to the trade data. WarenstromInfo (WI) was created as a software solution that allows easy trade data extraction and visualisation for application in different areas, such as outbreak investigations. WarenstromInfo (WI) is an application tool that automatically extracts, decodes and visually displays trade flow data from EUROSTAT "EU trade since 2002 by statistical procedure, by HS2-4-6 and CN8 (DS-059322)" (hereinafter referred to EUROSTAT) and the BACI databases, based on user input. WI was developed by using the open-source desktop software KNIME Analytics Platform. WI offers the flexibility to be executed either as a web service on a KNIME Web Server infrastructure or as a local resource. To integrate the BACI database into WI, the database is annually downloaded as csv files, rebuilt as a SQLite database and hosted locally into the KNIME Web Server Infrastructure. In order to optimise storage space on the KNIME server, this SQLite database specifically includes only agrifood data, reflecting the tool´s focus. However, if new objectives are established, this database can be expanded. Further, data of the SQLite database can be customised by executing the WI workflow locally, enabling the user to expand the database at any time. In contrast to BACI, trade data extraction from the EUROSTAT database is performed via the EUROSTAT’s API (Application Programming Interface) applying GET requests and XML data management. WI displays four User-friendly Interfaces (UIs) designed with interactive KNIME nodes that facilitate the input of variables. The extracted trade flow data are shown through interactive tables directly within the UIs. This feature enables users to easily explore the data in a structured and user-friendly manner. Additionally, WI incorporates the extracted trade flow data into maps. These maps provide a visual representation of the data, allowing users to gain insights and identify patterns and trends geographically. Both, the data table and the maps, can be downloaded as a single Excel file (containing multiple preformatted tables) and as png files, respectively.

Visualization of Covid-19 Data in Indonesia in 2022 through the Google Data Studio Dashboard

The COVID-19 pandemic has presented significant challenges to governments, researchers and the general public in understanding and monitoring the spread of this disease. In an effort to analyse the spread of COVID-19 disease in Indonesia effectively, this study uses Google Data Studio as a tool for data visualization and better understanding. This review is based on collecting data on the spread of COVID-19 disease in Indonesia which has been collected from various reliable sources. , including the World Health Organization (WHO) and national health agencies. This data is then processed and processed using Google Data Studio to produce informative visualizations. The results of the study show that Google Data Studio can be used effectively to analyse the spread of the COVID-19 disease in Indonesia. Through the use of available features, such as interactive graphs, maps, and tables, researchers can easily describe patterns of disease spread, infection rates, and recovery rates from an area or country. The quality of data collected from different sources may vary, and this can affect the accuracy and reliability of the resulting visualizations. Elements of the Scorecard that displays some important information related to the Covid-19 pandemic from 1 January 2019 to 31 January 2022. Information regarding the Covid-19 displayed on the Scorecard is as follows. The total survivors of the Covid-19 disease are 3,234,336,858 people. This indicates the number of people who have successfully recovered and recovered from infection with the Covid-19 virus during the period in question. The total number of deaths due to Covid-19 is 89,398,496 people. This reflects the number of people who died due to complications caused by the Covid-19 virus in that period.

ClusterV-Web: a user-friendly tool for profiling HIV quasispecies and generating drug resistance reports from nanopore long-read data.

Third-generation long-read sequencing is an increasingly utilized technique for profiling human immunodeficiency virus (HIV) quasispecies and detecting drug resistance mutations due to its ability to cover the entire viral genome in individual reads. Recently, the ClusterV tool has demonstrated accurate detection of HIV quasispecies from Nanopore long-read sequencing data. However, the need for scripting skills and a computational environment may act as a barrier for many potential users. To address this issue, we have introduced ClusterV-Web, a user-friendly web-based application that enables easy configuration and execution of ClusterV, both remotely and locally. Our tool provides interactive tables and data visualizations to aid in the interpretation of results. This development is expected to democratize access to long-read sequencing data analysis, enabling a wider range of researchers and clinicians to efficiently profile HIV quasispecies and detect drug resistance mutations. ClusterV-Web is freely available and open source, with detailed documentation accessible at http://www.bio8.cs.hku.hk/ClusterVW/. The standalone Docker image and source code are also available at https://github.com/HKU-BAL/ClusterV-Web.