Genome Analysis of SARS-CoV-2 Case Study: An Undergraduate Online Learning Activity To Introduce Bioinformatics, BLAST, and the Power of Genome Databases.
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ABSTRACT:
SUBMITTER: Steel JJ
PROVIDER: S-EPMC7976780 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundWith the advent of high throughput genotyping technology and the information available via projects such as the human genome sequencing and the HapMap project, more and more data relevant to the study of genetics and disease risk will be produced. Systematic reviews and meta-analyses of human genome epidemiology studies rely on the ability to identify relevant studies and to obtain suitable data from these studies. A first port of call for most such reviews is a search of MEDLINE. We examined whether this could be usefully supplemented by identifying databases on the World Wide Web that contain genetic epidemiological information.MethodsWe conducted a systematic search for online databases containing genetic epidemiological information on gene prevalence or gene-disease association. In those containing information on genetic association studies, we examined what additional information could be obtained to supplement a MEDLINE literature search.ResultsWe identified 111 databases containing prevalence data, 67 databases specific to a single gene and only 13 that contained information on gene-disease associations. Most of the latter 13 databases were linked to MEDLINE, although five contained information that may not be available from other sources.ConclusionThere is no single resource of structured data from genetic association studies covering multiple diseases, and in relation to the number of studies being conducted there is very little information specific to gene-disease association studies currently available on the World Wide Web. Until comprehensive data repositories are created and utilized regularly, new data will remain largely inaccessible to many systematic review authors and meta-analysts.
| S-EPMC1929117 | biostudies-literature
Project description:Anatomy and physiology instructors often face the daunting task of teaching the principles of neurophysiology as part of a laboratory course with very limited resources. Teaching neurophysiology can be a difficult undertaking as sophisticated electrophysiology and data acquisition equipment is often financially out-of-reach for two-year institutions, and for many preparations, instructors need to be highly skilled in electrophysiology techniques when teaching hands-on laboratories. In the absence of appropriate laboratory tools, many undergraduate students have difficulty understanding concepts related to neurophysiology. The cricket can serve as a reliable invertebrate model to teach the basic concepts of neurophysiology in the educational laboratory. In this manuscript, we describe a series of hands-on, demonstrative, technologically simple, and affordable laboratory activities that will help undergraduate students gain an understanding of the principles of neurophysiology. By using the cerci ganglion and leg preparation, students can quantify extracellular neural activity in response to sensory stimulation, understand the principles of rate coding and somatotopy, perform electrical microstimulation to understand the threshold of sensory stimulation, and do pharmacological manipulation of neuronal activity. We describe the utility of these laboratory activities, provide a convenient protocol for quantifying extracellular recordings, and discuss feedback provided by undergraduate students with regards to the quality of the educational experience after performing the lab activities.
| S-EPMC3852874 | biostudies-other
Project description:BackgroundMedical education all over the country has been forced to shift to e-learning, mainly online classes. In this scenario, the medical education department (MEU) of a teaching hospital under a deemed university felt the need to study the satisfaction and usefulness of these classes, as perceived by the undergraduate medical students.MethodsQuestionnaire survey was planned. A specially designed questionnaire was created, keeping in mind, the study objectives. It was validated, and a pilot was conducted, for modifications and to calculate sample size. The questionnaire was administered by email as Google Forms. The responses, which included quantitative and qualitative responses, were analysed, and feedback points noted. Percentage level of satisfaction and usefulness was calculated with 95% confidence interval. To test the statistical significance of the association of satisfaction levels amongst students of different Phases, chi square test was used.ResultsOn a scale scoring for satisfaction, 53.6% scored moderate, 31% high, and 15.4% low satisfaction. 49.8% of the students were less satisfied about attending classes from home; 15.7% felt it was better. 57.1% of the students found the concept of online learning moderately useful, 31.4% found it minimally useful, 11.5%, highly useful.ConclusionsThe undergraduate medical students perceived moderate satisfaction and usefulness with the on-going online classes. They expressed the desire to resume routine physical classes, especially for practicals and clinics. Points of improvement of the online teaching-learning programme were also obtained. This study revealed sufficient feedback to be shared with all stakeholders, regarding improvements in the online classes.
| S-EPMC7873757 | biostudies-literature
Project description:A dataset of 103 SARS-CoV isolates (101 human patients and 2 palm civets) was investigated on different aspects of genome polymorphism and isolate classification. The number and the distribution of single nucleotide variations (SNVs) and insertions and deletions, with respect to a "profile", were determined and discussed ("profile" being a sequence containing the most represented letter per position). Distribution of substitution categories per codon positions, as well as synonymous and non-synonymous substitutions in coding regions of annotated isolates, was determined, along with amino acid (a.a.) property changes. Similar analysis was performed for the spike (S) protein in all the isolates (55 of them being predicted for the first time). The ratio Ka/Ks confirmed that the S gene was subjected to the Darwinian selection during virus transmission from animals to humans. Isolates from the dataset were classified according to genome polymorphism and genotypes. Genome polymorphism yields to two groups, one with a small number of SNVs and another with a large number of SNVs, with up to four subgroups with respect to insertions and deletions. We identified three basic nine-locus genotypes: TTTT/TTCGG, CGCC/TTCAT, and TGCC/TTCGT, with four subgenotypes. Both classifications proposed are in accordance with the new insights into possible epidemiological spread, both in space and time.
| S-EPMC5172477 | biostudies-literature
Project description:The dynamic nature of technological developments invites us to rethink the learning spaces. In this context, science education can be enriched by the contribution of new computational resources, making the educational process more up-to-date, challenging, and attractive. Bioinformatics is a key interdisciplinary field, contributing to the understanding of biological processes that is often underrated in secondary schools. As a useful resource in learning activities, bioinformatics could help in engaging students to integrate multiple fields of knowledge (logical-mathematical, biological, computational, etc.) and generate an enriched and long-lasting learning environment. Here, we report our recent project in which high school students learned basic concepts of programming applied to solving biological problems. The students were taught the Python syntax, and they coded simple tools to answer biological questions using resources at hand. Notably, these were built mostly on the students' own smartphones, which proved to be capable, readily available, and relevant complementary tools for teaching. This project resulted in an empowering and inclusive experience that challenged differences in social background and technological accessibility.
| S-EPMC6375546 | biostudies-literature
Project description:Recent advances involving high-throughput techniques for data generation and analysis have made familiarity with basic bioinformatics concepts and programs a necessity in the biological sciences. Undergraduate students increasingly need training in methods related to finding and retrieving information stored in vast databases. The rapid rise of bioinformatics as a new discipline has challenged many colleges and universities to keep current with their curricula, often in the face of static or dwindling resources. On the plus side, many bioinformatics modules and related databases and software programs are free and accessible online, and interdisciplinary partnerships between existing faculty members and their support staff have proved advantageous in such efforts. We present examples of strategies and methods that have been successfully used to incorporate bioinformatics content into undergraduate curricula.
| S-EPMC2931662 | biostudies-literature
Project description:Relating behavioral and neuroimaging measures is essential to understanding human brain function. Often, this is achieved by computing a correlation between behavioral measures, e.g., reaction times, and neurophysiological recordings, e.g., prestimulus EEG alpha-power, on a single-trial-basis. This approach treats individual trials as independent measurements and ignores the fact that data are acquired in a temporal order. It has already been shown that behavioral measures as well as neurophysiological recordings display power-law dynamics, which implies that trials are not in fact independent. Critically, computing the correlation coefficient between two measures exhibiting long-range temporal dependencies may introduce spurious correlations, thus leading to erroneous conclusions about the relationship between brain activity and behavioral measures. Here, we address data-analytic pitfalls which may arise when long-range temporal dependencies in neural as well as behavioral measures are ignored. We quantify the influence of temporal dependencies of neural and behavioral measures on the observed correlations through simulations. Results are further supported in analysis of real EEG data recorded in a simple reaction time task, where the aim is to predict the latency of responses on the basis of prestimulus alpha oscillations. We show that it is possible to "predict" reaction times from one subject on the basis of EEG activity recorded in another subject simply owing to the fact that both measures display power-law dynamics. The same is true when correlating EEG activity obtained from different subjects. A surrogate-data procedure is described which correctly tests for the presence of correlation while controlling for the effect of power-law dynamics.
| S-EPMC6869015 | biostudies-literature
Project description:MOTIVATION:Data integration promises to be one of the main catalysts in enabling new insights to be drawn from the wealth of biological data available publicly. However, the heterogeneity of the different data sources, both at the syntactic and the semantic level, still poses significant challenges for achieving interoperability among biological databases. RESULTS:We introduce an ontology-based federated approach for data integration. We applied this approach to three heterogeneous data stores that span different areas of biological knowledge: (i) Bgee, a gene expression relational database; (ii) Orthologous Matrix (OMA), a Hierarchical Data Format 5 orthology DS; and (iii) UniProtKB, a Resource Description Framework (RDF) store containing protein sequence and functional information. To enable federated queries across these sources, we first defined a new semantic model for gene expression called GenEx. We then show how the relational data in Bgee can be expressed as a virtual RDF graph, instantiating GenEx, through dedicated relational-to-RDF mappings. By applying these mappings, Bgee data are now accessible through a public SPARQL endpoint. Similarly, the materialized RDF data of OMA, expressed in terms of the Orthology ontology, is made available in a public SPARQL endpoint. We identified and formally described intersection points (i.e. virtual links) among the three data sources. These allow performing joint queries across the data stores. Finally, we lay the groundwork to enable nontechnical users to benefit from the integrated data, by providing a natural language template-based search interface.
| S-EPMC6836710 | biostudies-literature
Project description:Comparing newly obtained and previously known nucleotide and amino-acid sequences underpins modern biological research. BLAST is a well-established tool for such comparisons but is challenging to use on new data sets. We combined a user-centric design philosophy with sustainable software development approaches to create Sequenceserver, a tool for running BLAST and visually inspecting BLAST results for biological interpretation. Sequenceserver uses simple algorithms to prevent potential analysis errors and provides flexible text-based and visual outputs to support researcher productivity. Our software can be rapidly installed for use by individuals or on shared servers.
| S-EPMC6878946 | biostudies-literature
Project description:Integrated studies of accumulated data can be performed to obtain more reliable information and more feasible measures for investigating the potential diagnostic and prognostic biomarkers of breast cancer and exploring related molecular mechanisms. Our study aimed to explore the GATA family members involved in breast cancer by integrating data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and other online databases. We performed an integrated analysis of published studies from GEO and analyzed clinical data from TCGA and GTEx to evaluate the clinical significance and prognosis values of the GATA family in breast cancer. GATA3 was found to be upregulated and exhibited a favorable value in the diagnosis and prognosis of breast cancer. Through this study, we identified possible GATA3-correlated genes and core pathways that play an important role, which requires further investigation in breast cancer.
| S-EPMC6418253 | biostudies-literature