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ABSTRACT:
SUBMITTER: Duvaud S
PROVIDER: S-EPMC8265094 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/. The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community.
| S-EPMC5080401 | biostudies-other
Project description:ObjectiveThe study sought to investigate whether consistent use of the Veterans Health Administration's My HealtheVet (MHV) online patient portal is associated with improvement in diabetes-related physiological measures among new portal users.Materials and methodsWe conducted a retrospective cohort study of new portal users with type 2 diabetes that registered for MHV between 2012 and 2016. We used random-effect linear regression models to examine associations between months of portal use in a year (consistency) and annual means of the physiological measures (hemoglobin A1c [HbA1c], low-density lipoproteins [LDLs], and blood pressure [BP]) in the first 3 years of portal use.ResultsFor patients with uncontrolled HbA1c, LDL, or BP at baseline, more months of portal use in a year was associated with greater improvement. Compared with 1 month of use, using the portal 12 months in a year was associated with annual declines in HbA1c of -0.41% (95% confidence interval [CI], -0.46% to -0.36%) and in LDL of -6.25 (95% CI, -7.15 to -5.36) mg/dL. Twelve months of portal use was associated with minimal improvements in BP: systolic BP of -1.01 (95% CI, -1.33 to -0.68) mm Hg and diastolic BP of -0.67 (95% CI, -0.85 to -0.49) mm Hg. All associations were smaller or not present for patients in control of these measures at baseline.ConclusionsWe found consistent use of the patient portal among new portal users to be associated with modest improvements in mean HbA1c and LDL for patients at increased risk at baseline. For patients with type 2 diabetes, self-management supported by online patient portals may help control HbA1c, LDL, and BP.
| S-EPMC8449618 | biostudies-literature
Project description:BackgroundWeb-based portals can enhance communication between patients and providers to support IBD self-management and improve care. We aimed to identify portal use patterns of patients with inflammatory bowel disease (IBD) to inform future web portal-based interventions and portal design.MethodsPatients with IBD receiving care at the University of Michigan between 2012 and 2021 were identified. Meta-data from electronic logs of each patient's most recent year of portal use were abstracted. Portal engagement was characterized in terms of intensity (ie, frequency of use); comprehensiveness (ie, number of portal functions used); and duration (ie, quarters per year of portal use). We used k-means clustering, a machine-learning technique, to identify groupings of portal users defined in terms of engagement features.ResultsWe found 5605 patients with IBD who had accessed their portal account at least once. The average age was 41.2 years (SD 16.7), 3035 (54.2%) were female, and 2214 (39.5%) received immune-targeted therapies. We identified 3 patterns of portal engagement: (1) low intensity users (29.5%); (2) moderate intensity, comprehensive, and sustained users (63.3%); and (3) high intensity, comprehensive, sustained users (7.2%). Patients with more intense, comprehensive, and sustained use of the portal were older, female, with more comorbidities, and were more likely to receive immune-targeted therapies.ConclusionUnderstanding distinct patterns of portal use can inform portal-based interventions and portal design. Patient portals may be particularly helpful in delivering assistance to those with comorbidities and those receiving immune-targeted therapies-many of whom demonstrate more intense, comprehensive, and sustained portal use.
| S-EPMC10769793 | biostudies-literature
Project description:BACKGROUND:A world first pineapple EST sequencing program has been undertaken to investigate genes expressed during non-climacteric fruit ripening and the nematode-plant interaction during root infection. Very little is known of how non-climacteric fruit ripening is controlled or of the molecular basis of the nematode-plant interaction. PineappleDB was developed to provide the research community with access to a curated bioinformatics resource housing the fruit, root and nematode infected gall expressed sequences. DESCRIPTION:PineappleDB is an online, curated database providing integrated access to annotated expressed sequence tag (EST) data for cDNA clones isolated from pineapple fruit, root, and nematode infected root gall vascular cylinder tissues. The database currently houses over 5600 EST sequences, 3383 contig consensus sequences, and associated bioinformatic data including splice variants, Arabidopsis homologues, both MIPS based and Gene Ontology functional classifications, and clone distributions. The online resource can be searched by text or by BLAST sequence homology. The data outputs provide comprehensive sequence, bioinformatic and functional classification information. CONCLUSION:The online pineapple bioinformatic resource provides the research community with access to pineapple fruit and root/gall sequence and bioinformatic data in a user-friendly format. The search tools enable efficient data mining and present a wide spectrum of bioinformatic and functional classification information. PineappleDB will be of broad appeal to researchers investigating pineapple genetics, non-climacteric fruit ripening, root-knot nematode infection, crassulacean acid metabolism and alternative RNA splicing in plants.
| S-EPMC1260026 | biostudies-literature
Project description:Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.
| S-EPMC5651980 | biostudies-literature
Project description:BackgroundPatient portals offer patients access to their medical information and tools to communicate with health care providers. It has been shown that patient portals have the potential to positively impact health outcomes and efficiency of health care. It is therefore important that health care organizations identify the patients who use or do not use the patient portal and explore the reasons in either case. The Unified Theory of Acceptance and Use of Technology (UTAUT) is a frequently used theory for explaining the use of information technology. It consists of the following constructs: performance expectancy, effort expectancy, social influence, facilitating conditions, and behavioral intention to use.ObjectiveThis study aimed to explore the prevalence of patient portal use and the characteristics of patients who use or do not use a patient portal. The main constructs of UTAUT, together with demographics and disease- and care-related characteristics, have been measured to explore the predictive factors of portal use.MethodsA cross-sectional study was conducted in the outpatient departments for adult patients of a university hospital in the Netherlands. Following outcomes were included: self-reported portal use, characteristics of users such as demographics, disease- and care-related data, eHealth literacy (modified score), and scores of UTAUT constructs. Descriptive analyses and univariate and multivariate logistic regression were also conducted.ResultsIn the analysis, 439 adult patients were included. Furthermore, 32.1% (141/439) identified as being a user of the patient portal; 31.2% (137/439) indicated as nonusers, but being aware of the existence of the portal; and 36.6% (161/439) as being nonusers not aware of the existence of the portal. In the entire study population, the factors of being chronically ill (odds ratio, OR 1.62, 95% CI 1.04-2.52) and eHealth literacy (modified score; OR 1.12, 95% CI 1.07-1.18) best predicted portal use. In users and nonusers who were aware of the portal, UTAUT constructs were added to the multivariate logistic regression, with chronically ill and modified eHealth literacy sum score. Effort expectancy (OR 13.02, 95% CI 5.68-29.87) and performance expectancy (OR 2.84, 95% CI 1.65-4.90) are shown to significantly influence portal use in this group.ConclusionsApproximately one-third of the patients of a university hospital self-reported using the patient portal; most expressed satisfaction. At first sight, being chronically ill and higher scores on the modified eHealth literacy scale explained portal use. Adding UTAUT constructs to the model revealed that effort expectancy (ease of use and knowledge and skills related to portal use) and performance expectancy (perceived usefulness) influenced portal use. Interventions to improve awareness of the portal and eHealth literacy skills of patients and further integration of the patient portal in usual face-to-face care are needed to increase use and potential subsequent patient benefits.
| S-EPMC6231740 | biostudies-literature
Project description:The peanut (Arachis hypogaea) is an important crop cultivated worldwide for oil production and food sources. Its complex genetic architecture (e.g., the large and tetraploid genome possibly due to unique cross of wild diploid relatives and subsequent chromosome duplication: 2n = 4x = 40, AABB, 2800 Mb) presents a major challenge for its genome sequencing and makes it a less-studied crop. Without a doubt, transcriptome sequencing is the most effective way to harness the genome structure and gene expression dynamics of this non-model species that has a limited genomic resource.With the development of next generation sequencing technologies such as 454 pyro-sequencing and Illumina sequencing by synthesis, the transcriptomics data of peanut is rapidly accumulated in both the public databases and private sectors. Integrating 187,636 Sanger reads (103,685,419 bases), 1,165,168 Roche 454 reads (333,862,593 bases) and 57,135,995 Illumina reads (4,073,740,115 bases), we generated the first release of our peanut transcriptome assembly that contains 32,619 contigs. We provided EC, KEGG and GO functional annotations to these contigs and detected SSRs, SNPs and other genetic polymorphisms for each contig. Based on both open-source and our in-house tools, PeanutDB presents many seamlessly integrated web interfaces that allow users to search, filter, navigate and visualize easily the whole transcript assembly, its annotations and detected polymorphisms and simple sequence repeats. For each contig, sequence alignment is presented in both bird's-eye view and nucleotide level resolution, with colorfully highlighted regions of mismatches, indels and repeats that facilitate close examination of assembly quality, genetic polymorphisms, sequence repeats and/or sequencing errors.As a public genomic database that integrates peanut transcriptome data from different sources, PeanutDB (http://bioinfolab.muohio.edu/txid3818v1) provides the Peanut research community with an easy-to-use web portal that will definitely facilitate genomics research and molecular breeding in this less-studied crop.
| S-EPMC3444431 | biostudies-literature
Project description:RPBS (Ressource Parisienne en Bioinformatique Structurale) is a resource dedicated primarily to structural bioinformatics. It is the result of a joint effort by several teams to set up an interface that offers original and powerful methods in the field. As an illustration, we focus here on three such methods uniquely available at RPBS: AUTOMAT for sequence databank scanning, YAKUSA for structure databank scanning and WLOOP for homology loop modelling. The RPBS server can be accessed at http://bioserv.rpbs.jussieu.fr/ and the specific services at http://bioserv.rpbs.jussieu.fr/SpecificServices.html.
| S-EPMC1160237 | biostudies-literature
Project description:Database URL:http://www.mirtoolsgallery.org.
| S-EPMC5819725 | biostudies-literature
Project description:Outbreaks of COVID-19 caused by the novel coronavirus SARS-CoV-2 is still a threat to global human health. In order to understand the biology of SARS-CoV-2 and developing drug against COVID-19, a vast amount of genomic, proteomic, interatomic, and clinical data is being generated, and the bioinformatics researchers produced databases, webservers and tools to gather those publicly available data and provide an opportunity of analyzing such data. However, these bioinformatics resources are scattered and researchers need to find them from different resources discretely. To facilitate researchers in finding the resources in one frame, we have developed an integrated web portal called OverCOVID (http://bis.zju.edu.cn/overcovid/). The publicly available webservers, databases and tools associated with SARS-CoV-2 have been incorporated in the resource page. In addition, a network view of the resources is provided to display the scope of the research. Other information like SARS-CoV-2 strains is visualized and various layers of interaction resources is listed in distinct pages of the web portal. As an integrative web portal, the OverCOVID will help the scientist to search the resources and accelerate the clinical research of SARS-CoV-2.
| S-EPMC8035963 | biostudies-literature