LIVIVO - Search results -

Search results

Result 1 - 10 of total 38

Search options

Article ; Online: Using a wearable patch to develop a digital monitoring biomarker of inflammation in response to LPS challenge.

Avey, Stefan / Chatterjee, Meenakshi / Manyakov, Nikolay V / Cooper, Philip / Sabins, Nina / Mosca, Kenneth / Mori, Simone / Baribaud, Frédéric / Morris, Mark / Lehar, Joseph / Deiteren, Annemie / Cossu, Marta / Smets, Sophie / Huizer, Tanja / Lamousé-Smith, Esi / Campbell, Kim / Pandis, Ioannis

Clinical and translational science

2024 Volume 17, Issue 2, Page(s) e13734

Abstract: Remote inflammation monitoring with digital health technologies (DHTs) would provide valuable information for both clinical research and care. Controlled perturbations of the immune system may reveal physiological signatures which could be used to ... ...

Abstract	Remote inflammation monitoring with digital health technologies (DHTs) would provide valuable information for both clinical research and care. Controlled perturbations of the immune system may reveal physiological signatures which could be used to develop a digital biomarker of inflammatory state. In this study, molecular and physiological profiling was performed following an in vivo lipopolysaccharide (LPS) challenge to develop a digital biomarker of inflammation. Ten healthy volunteers received an intravenous LPS challenge and were monitored for 24 h using the VitalConnect VitalPatch (VitalPatch). VitalPatch measurements included heart rate (HR), heart rate variability (HRV), respiratory rate (RR), and skin temperature (TEMP). Conventional episodic inpatient vital signs and serum proteins were measured pre- and post-LPS challenge. The VitalPatch provided vital signs that were comparable to conventional methods for assessing HR, RR, and TEMP. A pronounced increase was observed in HR, RR, and TEMP as well as a decrease in HRV 1-4 h post-LPS challenge. The ordering of participants by magnitude of inflammatory cytokine response 2 h post-LPS challenge was consistent with ordering of participants by change from baseline in vital signs when measured by VitalPatch (r = 0.73) but not when measured by conventional methods (r = -0.04). A machine learning model trained on VitalPatch data predicted change from baseline in inflammatory protein response (R
MeSH term(s)	Humans ; Lipopolysaccharides ; Vital Signs ; Inflammation/diagnosis ; Wearable Electronic Devices ; Biomarkers
Chemical Substances	Lipopolysaccharides ; Biomarkers
Language	English
Publishing date	2024-02-21
Publishing country	United States
Document type	Journal Article
ZDB-ID	2433157-0
ISSN	1752-8062 ; 1752-8054
ISSN (online)	1752-8062
ISSN	1752-8054
DOI	10.1111/cts.13734
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

Article: Using an electronic diary and wristband accelerometer to detect exacerbations and activity levels in COPD: a feasibility study.

Finney, Lydia J / Avey, Stefan / Wiseman, Dexter / Rowe, Anthony / Loza, Matthew J / Branigan, Patrick / Stevenson, Christopher S / Baribaud, Frédéric / Wedzicha, Jadwiga A / Pandis, Ioannis / Donaldson, Gavin C

ERJ open research

2023 Volume 9, Issue 6

Abstract: Background: Early and accurate identification of acute exacerbations of COPD may lead to earlier treatment and prevent hospital admission. Electronic diaries have been developed for symptom monitoring and accelerometers to monitor activity. However, it ... ...

Abstract	Background: Early and accurate identification of acute exacerbations of COPD may lead to earlier treatment and prevent hospital admission. Electronic diaries have been developed for symptom monitoring and accelerometers to monitor activity. However, it is unclear whether this technology is usable in the COPD population. This study aimed to assess the feasibility of an electronic diary (eDiary) for symptom reporting using the MoreCare app and activity monitoring with the Garmin Vivofit 2 in COPD. Methods: Participants were recruited from the London COPD Cohort. Participants were provided a Garmin Vivofit 2 activity monitor and an android tablet with the MoreCare app for a period of 3 months. Results: 25 COPD patients were recruited (mean±sd age 70.8±7.1 years, forced expiratory volume in 1 s (FEV Conclusions: Symptom and activity monitoring using digital technology is feasible in COPD. Further large-scale digital health studies are needed to assess whether eDiaries can be used to identify patients at risk of exacerbation and guide early intervention.
Language	English
Publishing date	2023-12-27
Publishing country	England
Document type	Journal Article
ZDB-ID	2827830-6
ISSN	2312-0541
ISSN	2312-0541
DOI	10.1183/23120541.00366-2023
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Identification of Fatigue and Sleepiness in Immune and Neurodegenerative Disorders from Measures of Real-World Gait Variability.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

2023 Volume 2023, Page(s) 1–4

Abstract: Current assessments of fatigue and sleepiness rely on patient reported outcomes (PROs), which are subjective and prone to recall bias. The current study investigated the use of gait variability in the "real world" to identify patient fatigue and daytime ... ...

Abstract	Current assessments of fatigue and sleepiness rely on patient reported outcomes (PROs), which are subjective and prone to recall bias. The current study investigated the use of gait variability in the "real world" to identify patient fatigue and daytime sleepiness. Inertial measurement units were worn on the lower backs of 159 participants (117 with six different immune and neurodegenerative disorders and 42 healthy controls) for up to 20 days, whom completed regular PROs. To address walking bouts that were short and sparse, four feature groups were considered: sequence-independent variability (SIV), sequence-dependant variability (SDV), padded SDV (PSDV), and typical gait variability (TGV) measures. These gait variability measures were extracted from step, stride, stance, and swing time, step length, and step velocity. These different approaches were compared using correlations and four machine learning classifiers to separate low/high fatigue and sleepiness.Most balanced accuracies were above 50%, the highest was 57.04% from TGV measures. The strongest correlation was 0.262 from an SDV feature against sleepiness. Overall, TGV measures had lower correlations and classification accuracies.Identifying fatigue or sleepiness from gait variability is extremely complex and requires more investigation with a larger data set, but these measures have shown performances that could contribute to a larger feature set.Clinical relevance- Gait variability has been repeatedly used to assess fatigue in the lab. The current study, however, explores gait variability for fatigue and daytime sleepiness in real-world scenarios with multiple gait-impacted disorders.
MeSH term(s)	Humans ; Disorders of Excessive Somnolence/diagnosis ; Disorders of Excessive Somnolence/etiology ; Disorders of Excessive Somnolence/physiopathology ; Fatigue/diagnosis ; Fatigue/etiology ; Fatigue/physiopathology ; Gait/physiology ; Immune System Diseases/complications ; Immune System Diseases/physiopathology ; Neurodegenerative Diseases/complications ; Neurodegenerative Diseases/physiopathology ; Sleepiness/physiology
Language	English
Publishing date	2023-12-12
Publishing country	United States
Document type	Clinical Study ; Journal Article ; Research Support, Non-U.S. Gov't
ISSN	2694-0604
ISSN (online)	2694-0604
DOI	10.1109/EMBC40787.2023.10339956
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article: Assessing fatigue and sleep in chronic diseases using physiological signals from wearables: A pilot study.

Frontiers in physiology

2022 Volume 13, Page(s) 968185

Abstract: Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the health-related quality of life (HRQoL). Currently, they are ... ...

Abstract	Problems with fatigue and sleep are highly prevalent in patients with chronic diseases and often rated among the most disabling symptoms, impairing their activities of daily living and the health-related quality of life (HRQoL). Currently, they are evaluated primarily
Language	English
Publishing date	2022-11-14
Publishing country	Switzerland
Document type	Journal Article
ZDB-ID	2564217-0
ISSN	1664-042X
ISSN	1664-042X
DOI	10.3389/fphys.2022.968185
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Stratification of asthma by lipidomic profiling of induced sputum supernatant.

Brandsma, Joost / Schofield, James P R / Yang, Xian / Strazzeri, Fabio / Barber, Clair / Goss, Victoria M / Koster, Grielof / Bakke, Per S / Caruso, Massimo / Chanez, Pascal / Dahlén, Sven-Erik / Fowler, Stephen J / Horváth, Ildikó / Krug, Norbert / Montuschi, Paolo / Sanak, Marek / Sandström, Thomas / Shaw, Dominick E / Chung, Kian Fan /

Singer, Florian / Fleming, Louise J / Adcock, Ian M / Pandis, Ioannis / Bansal, Aruna T / Corfield, Julie / Sousa, Ana R / Sterk, Peter J / Sánchez-García, Rubén J / Skipp, Paul J / Postle, Anthony D / Djukanović, Ratko

The Journal of allergy and clinical immunology

2023 Volume 152, Issue 1, Page(s) 117–125

Abstract: Background: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable ... ...

Abstract	Background: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. Objective: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. Methods: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. Results: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. Conclusion: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator.
MeSH term(s)	Humans ; Sputum/metabolism ; Lipidomics ; Proteomics/methods ; Cross-Sectional Studies ; Prospective Studies ; Asthma ; Lipids
Chemical Substances	Lipids
Language	English
Publishing date	2023-03-12
Publishing country	United States
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	121011-7
ISSN	1097-6825 ; 1085-8725 ; 0091-6749
ISSN (online)	1097-6825 ; 1085-8725
ISSN	0091-6749
DOI	10.1016/j.jaci.2023.02.032
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Accessible to users with ZB MED library card

In stock of ZB MED Cologne/Königswinter

Uh III Zs.92: Show issues

Location:
Je nach Verfügbarkeit (siehe Angabe bei Bestand)
bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
ab Jg. 2022: Lesesaal (EG)

Order via subito

Details ▾

Article ; Online: Optimising parallel R correlation matrix calculations on gene expression data using MapReduce.

Wang, Shicai / Pandis, Ioannis / Johnson, David / Emam, Ibrahim / Guitton, Florian / Oehmichen, Axel / Guo, Yike

BMC bioinformatics

2014 Volume 15, Page(s) 351

Abstract: Background: High-throughput molecular profiling data has been used to improve clinical decision making by stratifying subjects based on their molecular profiles. Unsupervised clustering algorithms can be used for stratification purposes. However, the ... ...

Abstract	Background: High-throughput molecular profiling data has been used to improve clinical decision making by stratifying subjects based on their molecular profiles. Unsupervised clustering algorithms can be used for stratification purposes. However, the current speed of the clustering algorithms cannot meet the requirement of large-scale molecular data due to poor performance of the correlation matrix calculation. With high-throughput sequencing technologies promising to produce even larger datasets per subject, we expect the performance of the state-of-the-art statistical algorithms to be further impacted unless efforts towards optimisation are carried out. MapReduce is a widely used high performance parallel framework that can solve the problem. Results: In this paper, we evaluate the current parallel modes for correlation calculation methods and introduce an efficient data distribution and parallel calculation algorithm based on MapReduce to optimise the correlation calculation. We studied the performance of our algorithm using two gene expression benchmarks. In the micro-benchmark, our implementation using MapReduce, based on the R package RHIPE, demonstrates a 3.26-5.83 fold increase compared to the default Snowfall and 1.56-1.64 fold increase compared to the basic RHIPE in the Euclidean, Pearson and Spearman correlations. Though vanilla R and the optimised Snowfall outperforms our optimised RHIPE in the micro-benchmark, they do not scale well with the macro-benchmark. In the macro-benchmark the optimised RHIPE performs 2.03-16.56 times faster than vanilla R. Benefiting from the 3.30-5.13 times faster data preparation, the optimised RHIPE performs 1.22-1.71 times faster than the optimised Snowfall. Both the optimised RHIPE and the optimised Snowfall successfully performs the Kendall correlation with TCGA dataset within 7 hours. Both of them conduct more than 30 times faster than the estimated vanilla R. Conclusions: The performance evaluation found that the new MapReduce algorithm and its implementation in RHIPE outperforms vanilla R and the conventional parallel algorithms implemented in R Snowfall. We propose that MapReduce framework holds great promise for large molecular data analysis, in particular for high-dimensional genomic data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new algorithm as a basis for optimising high-throughput molecular data correlation calculation for Big Data.
MeSH term(s)	Algorithms ; Cluster Analysis ; Gene Expression Profiling/methods ; High-Throughput Nucleotide Sequencing ; Humans ; Software
Language	English
Publishing date	2014-11-05
Publishing country	England
Document type	Evaluation Study ; Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-014-0351-9
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Article ; Online: Bioinformatic analysis of Entamoeba histolytica SINE1 elements.

Huntley, Derek M / Pandis, Ioannis / Butcher, Sarah A / Ackers, John P

BMC genomics

2010 Volume 11, Page(s) 321

Abstract: Background: Invasive amoebiasis, caused by infection with the human parasite Entamoeba histolytica remains a major cause of morbidity and mortality in some less-developed countries. Genetically E. histolytica exhibits a number of unusual features ... ...

Abstract	Background: Invasive amoebiasis, caused by infection with the human parasite Entamoeba histolytica remains a major cause of morbidity and mortality in some less-developed countries. Genetically E. histolytica exhibits a number of unusual features including having approximately 20% of its genome comprised of repetitive elements. These include a number of families of SINEs - non-autonomous elements which can, however, move with the help of partner LINEs. In many eukaryotes SINE mobility has had a profound effect on gene expression; in this study we concentrated on one such element - EhSINE1, looking in particular for evidence of recent transposition. Results: EhSINE1s were detected in the newly reassembled E. histolytica genome by searching with a Hidden Markov Model developed to encapsulate the key features of this element; 393 were detected. Examination of their sequences revealed that some had an internal structure showing one to four 26-27 nt repeats. Members of the different classes differ in a number of ways and in particular those with two internal repeats show the properties expected of fairly recently transposed SINEs - they are the most homogeneous in length and sequence, they have the longest (i.e. the least decayed) target site duplications and are the most likely to show evidence (in a cDNA library) of active transcription. Furthermore we were able to identify 15 EhSINE1s (6 pairs and one triplet) which appeared to be identical or very nearly so but inserted into different sites in the genome; these provide good evidence that if mobility has now ceased it has only done so very recently. Conclusions: Of the many families of repetitive elements present in the genome of E. histolytica we have examined in detail just one - EhSINE1. We have shown that there is evidence for waves of transposition at different points in the past and no evidence that mobility has entirely ceased. There are many aspects of the biology of this parasite which are not understood, in particular why it is pathogenic while the closely related species E. dispar is not, the great genetic diversity found amongst patient isolates and the fact, which may be related, that only a small proportion of those infected develop clinical invasive amoebiasis. Mobile genetic elements, with their ability to alter gene expression may well be important in unravelling these puzzles.
MeSH term(s)	Base Sequence ; Computational Biology ; Entamoeba histolytica/genetics ; Gene Duplication ; Genome, Protozoan/genetics ; Mutagenesis, Insertional/genetics ; Promoter Regions, Genetic/genetics ; RNA, Messenger/genetics ; Repetitive Sequences, Nucleic Acid/genetics ; Transcription, Genetic
Chemical Substances	RNA, Messenger
Language	English
Publishing date	2010-05-24
Publishing country	England
Document type	Journal Article
ISSN	1471-2164
ISSN (online)	1471-2164
DOI	10.1186/1471-2164-11-321
Database	MEDical Literature Analysis and Retrieval System OnLINE

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Bioinformatic analysis of Entamoeba histolytica SINE1 elements

Butcher Sarah A / Pandis Ioannis / Huntley Derek M / Ackers John P

BMC Genomics, Vol 11, Iss 1, p

2010 Volume 321

Abstract: Abstract Background Invasive amoebiasis, caused by infection with the human parasite Entamoeba histolytica remains a major cause of morbidity and mortality in some less-developed countries. Genetically E. histolytica exhibits a number of unusual features ...

Abstract	Abstract Background Invasive amoebiasis, caused by infection with the human parasite Entamoeba histolytica remains a major cause of morbidity and mortality in some less-developed countries. Genetically E. histolytica exhibits a number of unusual features including having approximately 20% of its genome comprised of repetitive elements. These include a number of families of SINEs - non-autonomous elements which can, however, move with the help of partner LINEs. In many eukaryotes SINE mobility has had a profound effect on gene expression; in this study we concentrated on one such element - EhSINE1, looking in particular for evidence of recent transposition. Results EhSINE1s were detected in the newly reassembled E. histolytica genome by searching with a Hidden Markov Model developed to encapsulate the key features of this element; 393 were detected. Examination of their sequences revealed that some had an internal structure showing one to four 26-27 nt repeats. Members of the different classes differ in a number of ways and in particular those with two internal repeats show the properties expected of fairly recently transposed SINEs - they are the most homogeneous in length and sequence, they have the longest (i.e. the least decayed) target site duplications and are the most likely to show evidence (in a cDNA library) of active transcription. Furthermore we were able to identify 15 EhSINE1s (6 pairs and one triplet) which appeared to be identical or very nearly so but inserted into different sites in the genome; these provide good evidence that if mobility has now ceased it has only done so very recently. Conclusions Of the many families of repetitive elements present in the genome of E. histolytica we have examined in detail just one - EhSINE1. We have shown that there is evidence for waves of transposition at different points in the past and no evidence that mobility has entirely ceased. There are many aspects of the biology of this parasite which are not understood, in particular why it is pathogenic while the closely related species E. dispar is not, the great genetic diversity found amongst patient isolates and the fact, which may be related, that only a small proportion of those infected develop clinical invasive amoebiasis. Mobile genetic elements, with their ability to alter gene expression may well be important in unravelling these puzzles.
Keywords	Genetics ; QH426-470 ; Biology (General) ; QH301-705.5 ; Science ; Q ; DOAJ:Genetics ; DOAJ:Biology ; DOAJ:Biology and Life Sciences ; Biotechnology ; TP248.13-248.65
Subject code	572
Language	English
Publishing date	2010-05-01T00:00:00Z
Publisher	BioMed Central
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: Stratification of asthma by lipidomic profiling of induced sputum supernatant

Brandsma, Joost / Schofield, James P.R. / Yang, Xian / Strazzeri, Fabio / Barber, Clair / Goss, Victoria M. / Koster, Grielof / Bakke, Per S. / Caruso, Massimo / Chanez, Pascal / Dahlén, Sven-Erik / Fowler, Stephen J. / Horváth, Ildikó / Krug, Norbert / Montuschi, Paolo / Sanak, Marek / Sandström, Thomas / Shaw, Dominick E. / Chung, Kian Fan /

Singer, Florian / Fleming, Louise J. / Adcock, Ian M. / Pandis, Ioannis / Bansal, Aruna T. / Corfield, Julie / Sousa, Ana R. / Sterk, Peter J. / Sánchez-García, Rubén J. / Skipp, Paul J. / Postle, Anthony D. / Djukanović, Ratko

2023

Abstract: 117 ... 125 ... Background: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to ... ...

Abstract	117 125 Background: Asthma is a chronic respiratory disease with significant heterogeneity in its clinical presentation and pathobiology. There is need for improved understanding of respiratory lipid metabolism in asthma patients and its relation to observable clinical features. Objective: We performed a comprehensive, prospective, cross-sectional analysis of the lipid composition of induced sputum supernatant obtained from asthma patients with a range of disease severities, as well as from healthy controls. Methods: Induced sputum supernatant was collected from 211 adults with asthma and 41 healthy individuals enrolled onto the U-BIOPRED (Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes) study. Sputum lipidomes were characterized by semiquantitative shotgun mass spectrometry and clustered using topologic data analysis to identify lipid phenotypes. Results: Shotgun lipidomics of induced sputum supernatant revealed a spectrum of 9 molecular phenotypes, highlighting not just significant differences between the sputum lipidomes of asthma patients and healthy controls, but also within the asthma patient population. Matching clinical, pathobiologic, proteomic, and transcriptomic data helped inform the underlying disease processes. Sputum lipid phenotypes with higher levels of nonendogenous, cell-derived lipids were associated with significantly worse asthma severity, worse lung function, and elevated granulocyte counts. Conclusion: We propose a novel mechanism of increased lipid loading in the epithelial lining fluid of asthma patients resulting from the secretion of extracellular vesicles by granulocytic inflammatory cells, which could reduce the ability of pulmonary surfactant to lower surface tension in asthmatic small airways, as well as compromise its role as an immune regulator. 152 1
Subject code	610
Language	English
Publishing country	de
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

Full text online

Full text

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Article ; Online: High dimensional biological data retrieval optimization with NoSQL technology.

Wang, Shicai / Pandis, Ioannis / Wu, Chao / He, Sijin / Johnson, David / Emam, Ibrahim / Guitton, Florian / Guo, Yike

BMC genomics

2014 Volume 15 Suppl 8, Page(s) S3

Abstract: Background: High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such ... ...

Abstract	Background: High-throughput transcriptomic data generated by microarray experiments is the most abundant and frequently stored kind of data currently used in translational medicine studies. Although microarray data is supported in data warehouses such as tranSMART, when querying relational databases for hundreds of different patient gene expression records queries are slow due to poor performance. Non-relational data models, such as the key-value model implemented in NoSQL databases, hold promise to be more performant solutions. Our motivation is to improve the performance of the tranSMART data warehouse with a view to supporting Next Generation Sequencing data. Results: In this paper we introduce a new data model better suited for high-dimensional data storage and querying, optimized for database scalability and performance. We have designed a key-value pair data model to support faster queries over large-scale microarray data and implemented the model using HBase, an implementation of Google's BigTable storage system. An experimental performance comparison was carried out against the traditional relational data model implemented in both MySQL Cluster and MongoDB, using a large publicly available transcriptomic data set taken from NCBI GEO concerning Multiple Myeloma. Our new key-value data model implemented on HBase exhibits an average 5.24-fold increase in high-dimensional biological data query performance compared to the relational model implemented on MySQL Cluster, and an average 6.47-fold increase on query performance on MongoDB. Conclusions: The performance evaluation found that the new key-value data model, in particular its implementation in HBase, outperforms the relational model currently implemented in tranSMART. We propose that NoSQL technology holds great promise for large-scale data management, in particular for high-dimensional biological data such as that demonstrated in the performance evaluation described in this paper. We aim to use this new data model as a basis for migrating tranSMART's implementation to a more scalable solution for Big Data.
MeSH term(s)	Database Management Systems ; Databases, Genetic ; High-Throughput Nucleotide Sequencing ; Humans ; Information Storage and Retrieval/methods ; Medical Informatics ; Multiple Myeloma/genetics ; Multiple Myeloma/metabolism ; Oligonucleotide Array Sequence Analysis ; Transcriptome
Language	English
Publishing date	2014
Publishing country	England
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ISSN	1471-2164
ISSN (online)	1471-2164
DOI	10.1186/1471-2164-15-S8-S3
Database	MEDical Literature Analysis and Retrieval System OnLINE

Full text online

Full text

Order via subito

Inter-library loan at ZB MED

Your chosen title can be delivered directly to ZB MED Cologne location if you are registered as a user at ZB MED Cologne.

Details ▾
- Full text online
- Order with fees

To top

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

More links

Kategorien

Order via subito

Full text online

More links

Kategorien

In stock of ZB MED Cologne/Königswinter

Order via subito

More links

Kategorien

Order via subito

More links

Kategorien

Order via subito

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Inter-library loan at ZB MED

Full text online

More links

Kategorien

Order via subito

Inter-library loan at ZB MED