The translational data analytics pipeline for large-scale MS imaging...
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Progress Report II
Progress Report V
Progress Report I
Progress Report I
Progress Report II
Translational Justice & Health Disparities Research in Genomics
COMMENTS
Translational Research in the Era of Precision Medicine: Where We Are and Where We Will Go
The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ineffective therapies and reduce adverse effects. The spread of "multi-omics" analysis and the ...
Data science in clinical and translational research: Improving the
In this themed issue of the Journal of Clinical and Translational Science, our goal was to curate a set of manuscripts that would highlight current innovations in data science that are of relevance to clinical and translational researchers.We planned to cover methodological advances, education, and the systems and processes by which data scientists contribute to clinical and translational ...
Big data in basic and translational cancer research
There are five basic data types in cancer research: molecular omics data, perturbation phenotypic data, molecular interaction data, imaging data, and textual data. Molecular omics data describe ...
Paradigm shift required for translational research on the brain
This study introduces a new translational research method that combines high-throughput analysis tools—which are techniques that can analyze a large amount of data quickly - like neuroimaging ...
Data and knowledge management in translational research: implementation
For large international research consortia, such as those funded by the European Union's Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential for the successful collection, organization and analysis of the resulting data. Research consortia are attempting ever more ambitious science to better understand disease, by leveraging ...
Translational research is all-encompassing and lets everyone be a
Everyone is a researcher. There is a huge value for all healthcare personnel and families to participate in research. Although career development is another important motivation, the advantages ...
A framework for clinical and translational research in the era ...
Abstract. Introduction: Rigor and reproducibility are two important cornerstones of medical and scientific advancement. Clinical and translational research (CTR) contains four phases (T1-T4), involving the translation of basic research to humans, then to clinical settings, practice, and the population, with the ultimate goal of improving public ...
The Use of Translational Research Platforms in Clinical and ...
Translational research platforms are publicly available solutions and are used to integrate data for analysis, anonymization and sharing. Exploiting openly accessible resources (i.e. studies published before November 2016) defining these tools, we established the key features and uses of each platform.
Translational Data Analytics
6701 Democracy Boulevard. Bethesda, MD 20892-4874. 301-594-8966. [email protected]. Our research activities involve the development of novel analysis methodologies of various types of research data and the application of such novel methodologies — or existing ones — to various translational research projects.
Applied Categorical Data Analysis and Translational Research
An updated treatment of categorical data analysis in the biomedical sciences that now explores applications to translational research. Thoroughly updated with the latest advances in the field, Applied Categorical Data Analysis and Translational Research, Second Edition maintains the accessible style of its predecessor while also exploring the importance of translational research as it relates ...
PDF Biomedical data analysis in translational research: Integration of
Biomedical data analysis in translational research,wehighlightrecentdevelop-ments and discuss current challenges in the following sections. Obviously, we 178 ESANN 2017 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 26-28 April 2017, i6doc.com publ., ISBN 978 ...
Extraction of relations between genes and diseases from text and large
The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. ... N. et al. Extraction of relations between genes and diseases from ...
Applied categorical data analysis and translational research
7 Categorical Data and Translational Research. 7.1 Types of Clinical Studies. 7.2 From Bioassays to Translational Research. 7.2.1 Analysis of In Vitro Experiments. 7.2.2 Design and Analysis of Experiments for Combination Therapy. 7.3 Phase I Clinical Trials. 7.3.1 Standard Design. 7.3.2 Fast Track Design. 7.3.3 Continual Reassessment Method. 7. ...
Translational research
Translational research (also called translation research, translational science, or, when the context is clear, simply translation) is research aimed at translating (converting) results in basic research into results that directly benefit humans. The term is used in science and technology, especially in biology and medical science.As such, translational research forms a subset of applied research.
Translational data analytics in exposure science and environmental
Background Translational data analytics aims to apply data analytics principles and techniques to bring about broader societal or human impact. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline. Methods We implemented a citizen-science project at a local high school ...
Abstract PS09-01: Individual patient data meta-analysis of clinical and
Individual patient data meta-analysis of clinical and translational biomarkers for prediction of pathological complete response (pCR) after de-escalated therapy in HER2+ breast cancer in four trials of the West German Study Group [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX.
Translational Research of the Acute Effects of Negative Emotions on
The critical analysis was the group × time (linear) interaction. For a sample size of 280 participants, the study had >80% power to detect the estimated effects for the primary outcome measures: RHI score, CD62E+ EMPs, and CD34+/CD133+/KDR+ cells. Please see Data S1 for further details about the SDs and correlations used to determine the ...
Comprehensive analysis of bulk and single-cell transcriptomic data
Identification of ER stress and lipid metabolism related genes. A Consensus clustering analysis of ER stress and lipid metabolic pathways, the TCGA data set is divided into two well-differentiated subgroups when k = 2.B This section describes related parameters of WGCNA analysis.C Heatmap and clustering of ssGSEA fractions of ER stress and lipid metabolism-related pathways.
Comprehensive characterization of stemness-related lncRNAs in triple
Background Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. Methods Utilizing RNA sequencing data and ...
Adult and pediatric relapsing multiple sclerosis phase II and phase III
Clinical and Translational Science is an open access translational research journal combining laboratory discoveries with the diagnosis and treatment of human disease. Abstract No systematic review of trial designs in patients with relapsing multiple sclerosis (RMS) was reported. ... Following analysis of OLE data from the RMS phase II study ...
Trends in big data analyses by multicenter collaborative translational
For this purpose, it is critical to conduct multicenter collaborative research across various fields, such as psychiatry, neuroscience, molecular biology, genomics, neuroimaging, cognitive science, neurophysiology, psychology, and pharmacology. Moreover, collaborative research plays an important role in the development of young researchers.
Multiomics analysis identifies oxidative phosphorylation as a cancer
A total of 30 LC-MS data from the 2-channel analysis (15 LC-MS data points, including three QC points in each channel) were exported. csv file using the Agilent MassHunter software. The exported data were uploaded to the IsoMS Pro 1.2.16. Data processing was performed after a quality check. The parameters used for data processing are as ...
Informatics Spotlight
The platform supports research efforts by enabling curation and analysis of data using the different components, as appropriate. ... The platform provides an inexpensive yet seamless way to translate clinical and translational research ideas into clinical applications for regions similar to Appalachia that have limited resources and a largely ...
Immersive lab seeks to bridge translational AI across a range of fields
Vanderbilt University has created a transformational lab focused on leveraging immersive translational AI to drive discovery across disciplines ranging from medicine and materials science to the ...
IMAGES
VIDEO
COMMENTS
The advent of Precision Medicine has globally revolutionized the approach of translational research suggesting a patient-centric vision with therapeutic choices driven by the identification of specific predictive biomarkers of response to avoid ineffective therapies and reduce adverse effects. The spread of "multi-omics" analysis and the ...
In this themed issue of the Journal of Clinical and Translational Science, our goal was to curate a set of manuscripts that would highlight current innovations in data science that are of relevance to clinical and translational researchers.We planned to cover methodological advances, education, and the systems and processes by which data scientists contribute to clinical and translational ...
There are five basic data types in cancer research: molecular omics data, perturbation phenotypic data, molecular interaction data, imaging data, and textual data. Molecular omics data describe ...
This study introduces a new translational research method that combines high-throughput analysis tools—which are techniques that can analyze a large amount of data quickly - like neuroimaging ...
For large international research consortia, such as those funded by the European Union's Horizon 2020 programme or the Innovative Medicines Initiative, good data coordination practices and tools are essential for the successful collection, organization and analysis of the resulting data. Research consortia are attempting ever more ambitious science to better understand disease, by leveraging ...
Everyone is a researcher. There is a huge value for all healthcare personnel and families to participate in research. Although career development is another important motivation, the advantages ...
Abstract. Introduction: Rigor and reproducibility are two important cornerstones of medical and scientific advancement. Clinical and translational research (CTR) contains four phases (T1-T4), involving the translation of basic research to humans, then to clinical settings, practice, and the population, with the ultimate goal of improving public ...
Translational research platforms are publicly available solutions and are used to integrate data for analysis, anonymization and sharing. Exploiting openly accessible resources (i.e. studies published before November 2016) defining these tools, we established the key features and uses of each platform.
6701 Democracy Boulevard. Bethesda, MD 20892-4874. 301-594-8966. [email protected]. Our research activities involve the development of novel analysis methodologies of various types of research data and the application of such novel methodologies — or existing ones — to various translational research projects.
An updated treatment of categorical data analysis in the biomedical sciences that now explores applications to translational research. Thoroughly updated with the latest advances in the field, Applied Categorical Data Analysis and Translational Research, Second Edition maintains the accessible style of its predecessor while also exploring the importance of translational research as it relates ...
Biomedical data analysis in translational research,wehighlightrecentdevelop-ments and discuss current challenges in the following sections. Obviously, we 178 ESANN 2017 proceedings, European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges (Belgium), 26-28 April 2017, i6doc.com publ., ISBN 978 ...
The application of BeFree to real-case scenarios shows its effectiveness in extracting information relevant for translational research. We show the value of the gene-disease associations extracted by BeFree through a number of analyses and integration with other data sources. ... N. et al. Extraction of relations between genes and diseases from ...
7 Categorical Data and Translational Research. 7.1 Types of Clinical Studies. 7.2 From Bioassays to Translational Research. 7.2.1 Analysis of In Vitro Experiments. 7.2.2 Design and Analysis of Experiments for Combination Therapy. 7.3 Phase I Clinical Trials. 7.3.1 Standard Design. 7.3.2 Fast Track Design. 7.3.3 Continual Reassessment Method. 7. ...
Translational research (also called translation research, translational science, or, when the context is clear, simply translation) is research aimed at translating (converting) results in basic research into results that directly benefit humans. The term is used in science and technology, especially in biology and medical science.As such, translational research forms a subset of applied research.
Background Translational data analytics aims to apply data analytics principles and techniques to bring about broader societal or human impact. Translational data analytics for environmental health is an emerging discipline and the objective of this study is to describe a real-world example of this emerging discipline. Methods We implemented a citizen-science project at a local high school ...
Individual patient data meta-analysis of clinical and translational biomarkers for prediction of pathological complete response (pCR) after de-escalated therapy in HER2+ breast cancer in four trials of the West German Study Group [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX.
The critical analysis was the group × time (linear) interaction. For a sample size of 280 participants, the study had >80% power to detect the estimated effects for the primary outcome measures: RHI score, CD62E+ EMPs, and CD34+/CD133+/KDR+ cells. Please see Data S1 for further details about the SDs and correlations used to determine the ...
Identification of ER stress and lipid metabolism related genes. A Consensus clustering analysis of ER stress and lipid metabolic pathways, the TCGA data set is divided into two well-differentiated subgroups when k = 2.B This section describes related parameters of WGCNA analysis.C Heatmap and clustering of ssGSEA fractions of ER stress and lipid metabolism-related pathways.
Background Cancer stem cells (CSCs) and long non-coding RNAs (lncRNAs) are known to play a crucial role in the growth, migration, recurrence, and drug resistance of tumor cells, particularly in triple-negative breast cancer (TNBC). This study aims to investigate stemness-related lncRNAs (SRlncRNAs) as potential prognostic indicators for TNBC patients. Methods Utilizing RNA sequencing data and ...
Clinical and Translational Science is an open access translational research journal combining laboratory discoveries with the diagnosis and treatment of human disease. Abstract No systematic review of trial designs in patients with relapsing multiple sclerosis (RMS) was reported. ... Following analysis of OLE data from the RMS phase II study ...
For this purpose, it is critical to conduct multicenter collaborative research across various fields, such as psychiatry, neuroscience, molecular biology, genomics, neuroimaging, cognitive science, neurophysiology, psychology, and pharmacology. Moreover, collaborative research plays an important role in the development of young researchers.
A total of 30 LC-MS data from the 2-channel analysis (15 LC-MS data points, including three QC points in each channel) were exported. csv file using the Agilent MassHunter software. The exported data were uploaded to the IsoMS Pro 1.2.16. Data processing was performed after a quality check. The parameters used for data processing are as ...
The platform supports research efforts by enabling curation and analysis of data using the different components, as appropriate. ... The platform provides an inexpensive yet seamless way to translate clinical and translational research ideas into clinical applications for regions similar to Appalachia that have limited resources and a largely ...
Vanderbilt University has created a transformational lab focused on leveraging immersive translational AI to drive discovery across disciplines ranging from medicine and materials science to the ...