scholarly journals OmixLitMiner: A Bioinformatics Tool for Prioritizing Biological Leads from ‘Omics Data Using Literature Retrieval and Data Mining

2020 ◽  
Vol 21 (4) ◽  
pp. 1374
Author(s):  
Pascal Steffen ◽  
Jemma Wu ◽  
Shubhang Hariharan ◽  
Hannah Voss ◽  
Vijay Raghunath ◽  
...  
Keyword(s):  
Large Scale ◽  
Keyword Search ◽  
Cancer Genomics ◽  
Biological Data ◽  
Strategic Decision ◽  
Future Research ◽  
Omics Data ◽  
Support Tool ◽  
New Knowledge

Proteomics and genomics discovery experiments generate increasingly large result tables, necessitating more researcher time to convert the biological data into new knowledge. Literature review is an important step in this process and can be tedious for large scale experiments. An informed and strategic decision about which biomolecule targets should be pursued for follow-up experiments thus remains a considerable challenge. To streamline and formalise this process of literature retrieval and analysis of discovery based ‘omics data and as a decision-facilitating support tool for follow-up experiments we present OmixLitMiner, a package written in the computational language R. The tool automates the retrieval of literature from PubMed based on UniProt protein identifiers, gene names and their synonyms, combined with user defined contextual keyword search (i.e., gene ontology based). The search strategy is programmed to allow either strict or more lenient literature retrieval and the outputs are assigned to three categories describing how well characterized a regulated gene or protein is. The category helps to meet a decision, regarding which gene/protein follow-up experiments may be performed for gaining new knowledge and to exclude following already known biomarkers. We demonstrate the tool’s usefulness in this retrospective study assessing three cancer proteomics and one cancer genomics publication. Using the tool, we were able to corroborate most of the decisions in these papers as well as detect additional biomolecule leads that may be valuable for future research.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-192 ◽  
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

scholarly journals Gender differences in utilization of services and tobacco cessation outcomes at a state quitline

2018 ◽  
Vol 9 (4) ◽  
pp. 663-668 ◽  
Author(s):  
Alicia M Allen ◽  
Nicole P Yuan ◽  
Betsy C Wertheim ◽  
Laurie Krupski ◽  
Melanie L Bell ◽  
...  
Keyword(s):  
Gender Differences ◽  
Tobacco Cessation ◽  
Large Scale ◽  
Scale Effects ◽  
Future Research ◽  
Utilization Of Services ◽  
Logistic Regression Models ◽  
Point Prevalence Abstinence ◽  
Current Tobacco

Abstract Research suggests that women may have poorer tobacco cessation outcomes than men; however, the literature is somewhat mixed. Less is known about gender differences in cessation within quitline settings. This study examined gender differences in the utilization of services (i.e., coaching sessions, pharmacotherapy) and tobacco cessation among callers to the Arizona Smokers’ Helpline (ASHLine). The study sample included callers enrolled in ASHLine between January 2011 and June 2016. We tracked number of completed coaching sessions. At the 7-month follow-up, callers retrospectively reported use of cessation pharmacotherapy (gum, patch, or lozenge), as well as current tobacco use. Associations between gender and tobacco cessation were tested using logistic regression models. At month 7, 36.4% of women (3,277/9,004) and 40.3% of men (2,960/7,341) self-reported 30-day point prevalence abstinence. Compared to men, fewer women reported using pharmacotherapy (women: 71.4% vs. men: 73.6%, p = .01) and completed at least five coaching sessions (women: 35.1% vs. men: 38.5%, p < .01). After adjusting for baseline characteristics, women had significantly lower odds of reporting tobacco cessation than men (OR = 0.91, 95% CI: 0.84 to 0.99). However, after further adjustment for use of pharmacotherapy and coaching, there was no longer a significant relationship between gender and tobacco cessation (OR: 0.96, 95% CI: 0.87 to 1.06). Fewer women than men reported tobacco cessation. Women also had lower utilization of quitline cessation services. Although the magnitude of these differences were small, future research on improving the utilization of quitline services among women may be worth pursuing given the large-scale effects of tobacco.

scholarly journals Implications for Future Research

2021 ◽  
pp. 161-189
Author(s):  
Xiu-bao Yu
Keyword(s):  
Decision Making ◽  
Decision Makers ◽  
Strategic Decision ◽  
Strategic Decision Making ◽  
Future Research ◽  
Decision Factors ◽  
Research Questions ◽  
The Impact

AbstractOn the basis of the three elements of strategy, this chapter puts forward some follow-up research questions and prospects mainly from the following aspects. The first is the study of factors that have influences on the quality of strategic decision. Factors include individual aspects of decision-maker, strategic decision-making information factors, approaches of strategic decision-making, etc. The second is about normative studies. They are about how the world ought to be or how strategy decisions ought to be in given situations. Outcomes of the studies can provide guidance to industry decision makers when facing development issues. Future research includePerhaps the impact of strategic decision-makers on the quality of strategies is far beyond our imagination.

scholarly journals The Multidimensional Benefits of University Student Volunteering: Psychological Contract, Expectations, and Outcomes

2019 ◽  
Vol 49 (1) ◽  
pp. 113-133 ◽  
Author(s):  
Debbie Haski-Leventhal ◽  
Megan Paull ◽  
Susan Young ◽  
Judith MacCallum ◽  
Kirsten Holmes ◽  
...  
Keyword(s):  
Nonprofit Organizations ◽  
Psychological Contract ◽  
Large Scale ◽  
University Student ◽  
Future Research ◽  
Stakeholder Groups ◽  
Unmet Expectations ◽  
Depth Analysis ◽  
New Knowledge ◽  
Australian Universities

Student volunteering has many benefits for students, universities, and nonprofit organizations (NPOs), but research on these from a multistakeholder perspective is scant. Using psychological contract theory, this article compares outcomes to expectations of students, universities, and NPOs, proposing a model of the benefits of volunteering to all three stakeholder groups. Based on a large-scale qualitative research with over 60 interviews in six Australian universities, the article offers an in-depth analysis of student volunteering benefits, surprises (benefits exceeding expectations), and disappointments (unmet expectations) for each stakeholder group. Some of these benefits align with existing literature, while others contribute new knowledge on the outcomes of student volunteering. The results show that training, preparation, and management of expectations have the potential to build positive benefits for all. It concludes with implications for universities and NPOs and directions for future research on student volunteering.

scholarly journals Predicting Age From Large-Scale Brain Networks: Evidence From the Cam-CAN Dataset Across the Lifespan

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 365-366
Author(s):  
Meghan Caulfield ◽  
Irene Kan ◽  
Evangelia Chrysikou
Keyword(s):  
Functional Connectivity ◽  
Cognitive Abilities ◽  
Large Scale ◽  
Explanatory Power ◽  
Future Research ◽  
Salience Network ◽  
Resting State Functional Connectivity ◽  
Older Adulthood ◽  
Age Cohort

Abstract Changes in cognition observed in aging (e.g. a shift from prioritization of fluid cognition in young adulthood toward an emphasis on crystalized knowledge and semantic cognition in older adulthood) are believed to reflect alterations in neural connectivity in aging. Recent work specifically highlights how increased connectivity between executive control (EC) regions and default mode network (DMN) may underlie characteristic shifts in cognitive abilities between younger and older adults. However, the contribution of the salience network, which plays a crucial role in mediating the dynamic interplay between EC and DMN, is relatively overlooked. To extend previous work, we used a large cohort (N = 547) of participants from the Cam-CAN database (18-88 years old) to examine whether resting-state functional connectivity between EC and DMN can reliably predict participant age. We further examined how addition of the salience network impacts the hypothesized increased connectivity between EC and DMN as a result of aging. A series of multiple regression analyses using functional connectivity and age as variables revealed that connectivity between EC and DMN regions (specifically between dorsolateral and ventromedial prefrontal cortex and parietal regions, including the precuneus) accounted for a significant portion of age variability and that the inclusion of the salience network improved the models’ explanatory power. Follow-up analyses by age cohort further highlighted that these relationships dynamically change across the lifespan. We will discuss these findings in the context of default-executive coupling hypothesis for aging and propose avenues for future research in refinement of this model.

scholarly journals BioNetComp: a Python package for biological network development and comparison

2021 ◽  
Author(s):  
Lucas Miguel Carvalho
Keyword(s):  
Biological Networks ◽  
Large Scale ◽  
Biological Network ◽  
Biological Data ◽  
Command Line ◽  
Omics Data ◽  
Network Development ◽  
Network Metrics ◽  
Web Platform ◽  
Python Package

Due to the large generation of omics data on a large scale in the last few years, the extraction of information from biological data has become more complex and its integration or comparison as well. One of the ways to represent interactions of biological data is through networks, which summarize information on interactions between their nodes through edges. The comparison of two biological networks using network metrics, biological enrichment, and visualization consists of data that allows us to understand differences in the interactomes of contrasting conditions. We describe BioNetComp, a python package to compare two different interactomes through different metrics and data visualization without the need for a web platform or software, just by command-line. As a result, we present a comparison made between the interactomes generated from the differentially expressed genes at two different points during a typical bioethanol fermentation. BioNetComp is available at github.com/lmigueel/BioNetComp.

scholarly journals Findings from the Section on Bioinformatics and Translational Informatics

2017 ◽  
Vol 26 (01) ◽  
pp. 188-191
Author(s):  
H. Dauchel ◽  
T. Lecroq
Keyword(s):  
Intelligent Systems ◽  
Large Scale ◽  
Cancer Genomics ◽  
Clinical Care ◽  
Evaluation Process ◽  
Omics Data ◽  
Health Domain ◽  
Medical Genomics ◽  
Research Activities ◽  
Translational Informatics

Summary Objective: To summarize excellent current research and propose a selection of best papers published in 2016 in the field of Bioinformatics and Translational Informatics with applications in the health domain and clinical care. Methods: We provide a synopsis of the articles selected for the IMIA Yearbook 2017, from which we attempt to derive a synthetic overview of current and future activities in the field. As in 2016, a first step of selection was performed by querying MEDLINE with a list of MeSH descriptors completed by a list of terms adapted to the section coverage. Each section editor evaluated separately the set of 951 articles returned and evaluation results were merged for retaining 15 candidate best papers for peer-review. Results: The selection and evaluation process of papers published in the Bioinformatics and Translational Informatics field yielded four excellent articles focusing this year on the secondary use and massive integration of multi-omics data for cancer genomics and non-cancer complex diseases. Papers present methods to study the functional impact of genetic variations, either at the level of the transcription or at the levels of pathway and network. Conclusions: Current research activities in Bioinformatics and Translational Informatics with applications in the health domain continue to explore new algorithms and statistical models to manage, integrate, and interpret large-scale genomic datasets. As addressed by some of the selected papers, future trends would include the question of the international collaborative sharing of clinical and omics data, and the implementation of intelligent systems to enhance routine medical genomics.

scholarly journals mixOmics: an R package for ‘omics feature selection and multiple data integration

2017 ◽  
Author(s):  
Florian Rohart ◽  
Benoît Gautier ◽  
Amrit Singh ◽  
Kim-Anh Lê Cao
Keyword(s):  
Data Integration ◽  
Large Scale ◽  
Relevant Information ◽  
R Package ◽  
Biological Data ◽  
Molecular Signature ◽  
Single Type ◽  
Data Sets ◽  
Omics Data ◽  
Wide Range

AbstractThe advent of high throughput technologies has led to a wealth of publicly available ‘omics data coming from different sources, such as transcriptomics, proteomics, metabolomics. Combining such large-scale biological data sets can lead to the discovery of important biological insights, provided that relevant information can be extracted in a holistic manner. Current statistical approaches have been focusing on identifying small subsets of molecules (a ‘molecular signature’) to explain or predict biological conditions, but mainly for a single type of ‘omics. In addition, commonly used methods are univariate and consider each biological feature independently.We introducemixOmics, an R package dedicated to the multivariate analysis of biological data sets with a specific focus on data exploration, dimension reduction and visualisation. By adopting a system biology approach, the toolkit provides a wide range of methods that statistically integrate several data sets at once to probe relationships between heterogeneous ‘omics data sets. Our recent methods extend Projection to Latent Structure (PLS) models for discriminant analysis, for data integration across multiple ‘omics data or across independent studies, and for the identification of molecular signatures. We illustrate our latestmixOmicsintegrative frameworks for the multivariate analyses of ‘omics data available from the package.

scholarly journals Integrated Solutions for the Water-Energy-Land Nexus: Are Global Models Rising to the Challenge?

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2223 ◽  
Author(s):  
Nils Johnson ◽  
Peter Burek ◽  
Edward Byers ◽  
Giacomo Falchetta ◽  
Martina Flörke ◽  
...  
Keyword(s):  
Integrated Assessment ◽  
Large Scale ◽  
Keyword Search ◽  
Relevant Literature ◽  
Model Development ◽  
Global Scale ◽  
Future Research ◽  
Implementation Challenges ◽  
Trade Offs

Increasing human demands for water, energy, food and materials, are expected to accentuate resource supply challenges over the coming decades. Experience suggests that long-term strategies for a single sector could yield both trade-offs and synergies for other sectors. Thus, long-term transition pathways for linked resource systems should be informed using nexus approaches. Global integrated assessment models can represent the synergies and trade-offs inherent in the exploitation of water, energy and land (WEL) resources, including the impacts of international trade and climate policies. In this study, we review the current state-of-the-science in global integrated assessment modeling with an emphasis on how models have incorporated integrated WEL solutions. A large-scale assessment of the relevant literature was performed using online databases and structured keyword search queries. The results point to the following main opportunities for future research and model development: (1) improving the temporal and spatial resolution of economic models for the energy and water sectors; (2) balancing energy and land requirements across sectors; (3) integrated representation of the role of distribution infrastructure in alleviating resource challenges; (4) modeling of solution impacts on downstream environmental quality; (5) improved representation of the implementation challenges stemming from regional financial and institutional capacity; (6) enabling dynamic multi-sectoral vulnerability and adaptation needs assessment; and (7) the development of fully-coupled assessment frameworks based on consistent, scalable, and regionally-transferable platforms. Improved database management and computational power are needed to address many of these modeling challenges at a global-scale.

scholarly journals Differences in the presentation and progression of Parkinson’s disease by sex

2020 ◽  
Author(s):  
Hirotaka Iwaki ◽  
Cornelis Blauwendraat ◽  
Hampton L. Leonard ◽  
Mary B. Makarious ◽  
Jonggeol J. Kim ◽  
...  
Keyword(s):  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Large Scale ◽  
Rating Scale ◽  
Underlying Mechanism ◽  
Future Research ◽  
Disease Heterogeneity ◽  
Cox Models ◽  
Logistic Regression Models

AbstractObjectivesIdentifying the contribution of biological sex to the heterogeneity in presentation and progression of Parkinson’s disease (PD).BackgroundThe different prevalence of Parkinson’s disease (PD) in men and women suggests that sex-associated mechanisms influence disease mechanisms. Investigating the contribution of sex to disease heterogeneity may uncover disease processes, and lead to new therapeutic targets. Also, understanding these differences in phenotypes will result in better patient management and the planning of more efficient clinical trials.MethodsWe tested 40 clinical phenotypes using longitudinal clinic-based patient cohorts consisting of 5,946 patients with a median follow-up of 3.1 years. For continuous outcomes, we used linear regressions at baseline to test the sex-associated differences in presentation, and linear mixed-effects models to test the sex-associated differences in progression. For binomial outcomes, we used logistic regression models at baseline and Cox models for survival analyses. We adjusted for age, disease duration and dopaminergic medication usage. In the secondary analyses, data from 28,809 PD patients and 10,556 non-PD participants from Fox Insight, an online-only self-assessment cohort for PD research, were analyzed to check whether the sex-associated differences observed in the primary analyses were consistent in the cohort and whether the differences were unique to PD or not.ResultsFemale PD patients had a higher risk for developing dyskinesia early during the follow-up period; with a slower progression in their difficulties of activities of daily living as measured by the Unified Parkinson’s Disease Rating Scale Part II (classic/MDS-revised version); and a lower risk of developing cognitive impairment than male patients. The findings in the longitudinal clinic-based cohorts were mostly consistent with the results in the online-only cohort.ConclusionsThis large-scale analysis observed the sex contribution to the heterogeneity of Parkinson’s disease. The results highlight the necessity of future research of the underlying mechanism and importance of personalized clinical management.

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