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Genomics and Systems Biology Approaches in the Study of Lipid Disorders
2018
Revista de investigación clínica
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To better address the complex genetic architecture and multiple properties leading to high serum lipid levels, networks and systems approach combining information at genomic, transcriptomics, methylomics ...
High serum lipid levels, specifically high levels of serum low-density lipoprotein cholesterol and triglycerides, are well-established key risk factors of atherosclerosis. ...
Furthermore, exome sequencing and whole genome sequencing using efficient and large-scale massive parallel sequencing approaches enable the identification of the full spectrum of variants, including rare ...
doi:10.24875/ric.18002576
pmid:30307448
fatcat:mbbuqcfqendmfdgznt4vvczkbe
Statistical and Machine Learning Approaches to Predict Gene Regulatory Networks From Transcriptome Datasets
2018
Frontiers in Plant Science
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Statistical and machine learning (ML)-based methods have recently advanced in construction of gene regulatory network (GRNs) based on high-throughput biological datasets. ...
This review summarizes the recent advancements in the computational inference of GRNs, based on large-scale transcriptome sequencing datasets of model plants and crops. ...
, by comparing it with previously identified regulatory network based on the results from ChIP-seq analysis and RNA-Seq analysis of its mutants. ...
doi:10.3389/fpls.2018.01770
pmid:30555503
pmcid:PMC6281826
fatcat:phaqyh5odvf4nkcwrwiqstoz2i
Discriminating dietary responses by combining transcriptomics and metabolomics data in nutrition intervention studies
2020
Molecular Nutrition & Food Research
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We investigated the performance of two data integration tools, "SNFtool" and "DIABLO" (MixOmics), in discriminating responses to diet and metabolic phenotypes by combining transcriptomics and metabolomics ...
For studies 2 and 3, the value of SNF integration depended on the dietary groups being compared, while DIABLO discriminated samples well but did not perform better than transcriptomic data alone. ...
Study 2 was funded by the National Children's Research Centre, Crumlin, Ireland (Grant number: ...
doi:10.1002/mnfr.202000647
pmid:33325641
fatcat:zrwajcdzdjdxvhdqbdhvxwrib4
MATTE: anti-noise module alignment for phenotype-gene-related analysis
[article]
2022
bioRxiv
pre-print
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Methods: The study developed a method to directly compare the transcriptome data of phenotypes and present the differences modularly, called Module Alignment of TranscripTomE(MATTE). ...
Purpose: Although many transcriptome analysis methods find fundamental interactions or markers of some phenotypes, preservation of module or network is still a challenge. ...
The source code of MATTE and case analysis can be found on Github(https://github.com/zjupgx/MATTE). ...
doi:10.1101/2022.05.29.493935
fatcat:efxgzo5ra5bgdgg6vqibnoc3k4
Toward Systems Biology in Brown Algae to Explore Acclimation and Adaptation to the Shore Environment
2011
Omics
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After giving some insights on recent stress omics data produced in Ectocarpus, we describe a gradual approach that will consist in inferring metabolic networks by integrating different levels of knowledge ...
Systems biology approaches can be applied to study different levels of cell organization (cell, tissue, whole plant, population), and we have chosen to focus this review on analysis at the cellular scale ...
Several techniques, mainly based on decomposition of the fluxes going through the metabolic network into a set of elementary flux modes, allow to analyze the metabolic flux of a balanced metabolic system ...
doi:10.1089/omi.2011.0089
pmid:22136637
fatcat:h7szzo46gvbppo74ypjem2qmyu
Heart failure: a complex clinical process interpreted by systems biology approach and network medicine
2014
Anadolu Kardiyoloji Dergisi/The Anatolian Journal of Cardiology
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The classical description of heart failure is based on tissue pathology and clinical presentation, and lately on specific genetic and molecular modifications. ...
Systems biology detects and evaluates specific networks from molecular, cellular and tissue elements, and assesses their influence on the appearance of clinical phenotypes. ...
Conflict of interest: None declared. Peer-review: Externally peer-reviewed. ...
doi:10.5152/akd.2014.5091
pmid:24566513
fatcat:67soxgzv4vdmzih665atooot7y
RNA-Seq Data: A Complexity Journey
2014
Computational and Structural Biotechnology Journal
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A paragraph from the highlights of "Transcriptomics: Throwing light on dark matter" by L. ...
However, much less attention has been turned to the problem of deciphering the complexity of transcriptome data, which determines uncertainty with regard to identification, quantification and differential ...
Acknowledgments The author thanks his colleagues at the University of Miami for fruitful discussions on the topics addressed in this review. ...
doi:10.1016/j.csbj.2014.09.004
pmid:25408846
pmcid:PMC4232570
fatcat:znwwul6f5jhhffd73lry2apo6u
Algorithmic and analytical methods in network biology
2009
Wiley Interdisciplinary Reviews: Systems Biology and Medicine
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, including the following: (1) inference and reconstruction of complex cellular networks; (2) identification of common and coherent patterns in cellular networks, with a view to understanding the organizing ...
The past decade witnessed significant efforts on the development of computational infrastructure for large-scale modeling and analysis of biological systems, commonly using network models. ...
This work was also supported, in part, by the National Institutes of Health Grant, UL1-RR024989 Supplement, from the National Center for Research Resources (Clinical and Translational Science Awards). ...
doi:10.1002/wsbm.61
pmid:20836029
pmcid:PMC3087298
fatcat:hfrwmgltzbht5hmwwea4uabjki
Towards a Quantitative Understanding of Cell Identity
2018
Trends in Cell Biology
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Cells have traditionally been characterized using expression levels of a few proteins that are thought to specify phenotype. ...
Collectively, these concepts are essential for constructing quantitative phenotypic landscapes, which will enhance our understanding of cell biology and facilitate cell engineering for research and clinical ...
Compared to the core TF identification method described above, Mogrify is more comprehensive since it uses the entire transcriptomic profile instead of a pre-selected pool of TFs. ...
doi:10.1016/j.tcb.2018.09.002
pmid:30309735
pmcid:PMC6249108
fatcat:fbygtjkw4relhm6yizbn52sej4
Understanding the Molecular Mechanisms of Asthma through Transcriptomics
2020
Allergy Asthma and Immunology Research
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The transcriptome represents the complete set of RNA transcripts that are produced by the genome under a specific circumstance or in a specific cell. ...
In this manuscript, we briefly review how to analyze transcriptome data and then provide a summary of recent transcriptome studies focusing on asthma pathogenesis and asthma drug responses. ...
An increasingly attractive approach is to focus on an individual cell type or to use single cell RNAseq in order to do cellular decomposition of whole blood. ...
doi:10.4168/aair.2020.12.3.399
pmid:32141255
pmcid:PMC7061151
fatcat:4u7pwjzpunav7i3fcsj2jnipqu
Systems Medicine as an Emerging Tool for Cardiovascular Genetics
2016
Frontiers in Cardiovascular Medicine
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The invention of arrays and analysis of multiple case-control samples have led to the identification of numerous genetic variants associated with coronary artery disease (CAD) risk. ...
DNA sequencing and assembling is one of the most prominent techniques in genomics. ...
These include the identification of network scaffolds by delineating existing interactions between cellular components, the decomposition of such network scaffolds into constituent parts, and the development ...
doi:10.3389/fcvm.2016.00027
pmid:27626034
pmcid:PMC5003874
fatcat:s5uya6do65f25k4qy6tejhlqgy
DRIM: A Web-Based System for Investigating Drug Response at the Molecular Level by Condition-Specific Multi-Omics Data Integration
2020
Frontiers in Genetics
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One effective way is to interpret transcriptome data in terms of well-characterized biological pathways. Another way is to leverage state-of-the-art methods for multi-omics data integration. ...
For the multi-omics perspective analysis, IC 50-related multi-omics potential mediator genes are determined by embedding multi-omics data to gene-centric vector space using a tensor decomposition method ...
Differential regulatory Network-based Modeling and Characterization (DryNetMC) (Zhang et al., 2019 ) is a network-based algorithm to detect key cancer resistance genes based on time-series RNA-seq data ...
doi:10.3389/fgene.2020.564792
pmid:33281870
pmcid:PMC7689278
fatcat:7i6jpu67ufcs3lw4nictxtpdxy
Computational biology approaches for mapping transcriptional regulatory networks
2021
Computational and Structural Biotechnology Journal
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by type of methodological approach. ...
Transcriptional Regulatory Networks (TRNs) are mainly responsible for the cell-type or cell-state -specific expression of gene sets from the same DNA sequence. ...
First based on bulk transcriptomic data, different mathematical modelling methods have been tested and compared, in particular during the DREAM challenges. ...
doi:10.1016/j.csbj.2021.08.028
pmid:34522292
pmcid:PMC8426465
fatcat:radqgznjybfo7iey55vjd2ntwm
AutoSOME: a clustering method for identifying gene expression modules without prior knowledge of cluster number
2010
BMC Bioinformatics
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proteinprotein interaction network characterizing pluripotency was underestimated by a factor of four. ...
Unfortunately, the underlying structure of these natural datasets is often fuzzy, and the computational identification of data clusters generally requires knowledge about cluster number and geometry. ...
Transcriptome clustering of this dataset using a bootstrapped version of nNMF, followed by a comparison of transcriptome classes for significantly enriched interaction networks, was used to identify PluriNet ...
doi:10.1186/1471-2105-11-117
pmid:20202218
pmcid:PMC2846907
fatcat:xvn5an5irvef3kopmbl5lfth6q
Circadian Control of Global Gene Expression Patterns
2010
Annual Review of Genetics
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Here, we review the impacts transcriptomics have had on our understanding of the clock and how this molecular clock connects with system-level circadian responses. ...
We explore the discoveries made possible by high-throughput RNA assays, the network approaches used to investigate these large transcript datasets, and potential future directions. ...
COMBINING THE TRANSCRIPTOME WITH THE GENOME TO DEVELOP CIS-
REGULATORY NETWORKS One of the most direct applications of expression data is the identification and integration of cis-regulatory elements ...
doi:10.1146/annurev-genet-102209-163432
pmid:20809800
pmcid:PMC4251774
fatcat:l6dhwlcoajegnnchgcp2tdxpvm
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