scholarly journals Whole-genome approaches for large-scale gene identification and expression analysis in mammalian preimplantation embryos

2005 ◽  
Vol 17 (2) ◽  
pp. 37 ◽  
Author(s):  
James Adjaye
Keyword(s):  
Systems Biology ◽  
Molecular Biology ◽  
Regenerative Medicine ◽  
High Throughput ◽  
Molecular Basis ◽  
Large Scale ◽  
Transcriptional Control ◽  
Preimplantation Embryos ◽  
Gene Identification ◽  
Whole Genome

The elucidation, unravelling and understanding of the molecular basis of transcriptional control during preimplantion development is of utmost importance if we are to intervene and eliminate or reduce abnormalities associated with growth, disease and infertility by applying assisted reproduction. Importantly, these studies should enhance our knowledge of basic reproductive biology and its application to regenerative medicine and livestock production. A major obstacle impeding progress in these areas is the ability to successfully generate molecular portraits of preimplantation embryos from their minute amounts of RNA. The present review describes the various approaches whereby classical embryology fuses with molecular biology, high-throughput genomics and systems biology to address and solve questions related to early development in mammals.

Benefits and harms of wellness initiatives

2019 ◽  
Vol 57 (10) ◽  
pp. 1494-1500 ◽  
Author(s):  
Clare Fiala ◽  
Jennifer Taher ◽  
Eleftherios P. Diamandis
Keyword(s):  
Health Care ◽  
Systems Biology ◽  
Large Scale ◽  
Whole Genome ◽  
Healthy Individuals ◽  
Therapeutic Measures ◽  
Limited Health ◽  
Wellness Initiatives ◽  
Healthy Participants ◽  
Selection Of

Abstract Wellness projects are large scale studies of healthy individuals through extensive laboratory and other testing. The “Hundred Person Wellness Study”, was one of the first to report results and lessons from its approach and these lessons can be applied to other wellness projects which are being undertaken by major companies and other organizations. In the “Hundred Person Wellness Study”, investigators from the Institute for Systems Biology (ISB) sequenced the genome, and analyzed the blood, saliva, urine and microbiome of 108 healthy participants every 3 months, for 9 months, to look for subtle changes signifying the transition to disease. We discuss some of the possible shortcomings of this approach; questioning the need to “improve” biomarker levels, excessive testing leading to over-diagnosis and over-treatment, expected results and improvements, selection of tests, problems with whole genome sequencing and speculations on therapeutic measures. We hope this discussion will lead to a continued evaluation of wellness interventions, leading to strategies that truly benefit patients within the constraint of limited health care resources.

scholarly journals LipidLynxX: a data transfer hub to support integration of large scale lipidomics datasets

2020 ◽  
Author(s):  
Zhixu Ni ◽  
Maria Fedorova
Keyword(s):  
Systems Biology ◽  
Data Integration ◽  
High Throughput ◽  
Large Scale ◽  
Data Transfer ◽  
Structural Information ◽  
Meta Analysis ◽  
Health And Disease ◽  
Different Levels ◽  
Cross Match

AbstractModern high throughput lipidomics provides large-scale datasets reporting hundreds of lipid molecular species. However, cross-laboratory comparison, meta-analysis, and systems biology integration of in-house generated and published datasets remain challenging due to a high diversity of used lipid annotation systems, different levels of reported structural information, and shortage in links to data integration resources. To support lipidomics data integration and interoperability of experimental lipidomics with data integration tools, we developed LipidLynxX serving as a hub facilitating data flow from high-throughput lipidomics analysis to systems biology data integration. LipidLynxX provides the possibility to convert, cross-match, and link various lipid annotations to the tools supporting lipid ontology, pathway, and network analysis aiming systems-wide integration and functional annotation of lipidome dynamics in health and disease. LipidLynxX is a flexible, customizable open-access tool freely available for download at https://github.com/SysMedOs/LipidLynxX.

scholarly journals Plant Proteomic Research 4.0: Frontiers in Stress Resilience

2021 ◽  
Vol 22 (24) ◽  
pp. 13362
Author(s):  
Sixue Chen ◽  
Setsuko Komatsu
Keyword(s):  
Systems Biology ◽  
High Throughput ◽  
Large Scale ◽  
Stress Resilience ◽  
Omics Technologies ◽  
Proteomic Research

Large-scale high-throughput multi-omics technologies are indispensable components of systems biology in terms of discovering and defining parts of the system [...]

scholarly journals High-Throughput Large-Scale Targeted Proteomics Assays for Quantifying Pathway Proteins in Pseudomonas putida KT2440

2020 ◽  
Vol 8 ◽  
Author(s):  
Yuqian Gao ◽  
Thomas L. Fillmore ◽  
Nathalie Munoz ◽  
Gayle J. Bentley ◽  
Christopher W. Johnson ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Systems Biology ◽  
Pseudomonas Putida ◽  
High Throughput ◽  
High Speed ◽  
Large Scale ◽  
Protein Quantification ◽  
Selected Reaction Monitoring ◽  
Targeted Proteomics ◽  
Pseudomonas Putida Kt2440

Targeted proteomics is a mass spectrometry-based protein quantification technique with high sensitivity, accuracy, and reproducibility. As a key component in the multi-omics toolbox of systems biology, targeted liquid chromatography-selected reaction monitoring (LC-SRM) measurements are critical for enzyme and pathway identification and design in metabolic engineering. To fulfill the increasing need for analyzing large sample sets with faster turnaround time in systems biology, high-throughput LC-SRM is greatly needed. Even though nanoflow LC-SRM has better sensitivity, it lacks the speed offered by microflow LC-SRM. Recent advancements in mass spectrometry instrumentation significantly enhance the scan speed and sensitivity of LC-SRM, thereby creating opportunities for applying the high speed of microflow LC-SRM without losing peptide multiplexing power or sacrificing sensitivity. Here, we studied the performance of microflow LC-SRM relative to nanoflow LC-SRM by monitoring 339 peptides representing 132 enzymes in Pseudomonas putida KT2440 grown on various carbon sources. The results from the two LC-SRM platforms are highly correlated. In addition, the response curve study of 248 peptides demonstrates that microflow LC-SRM has comparable sensitivity for the majority of detected peptides and better mass spectrometry signal and chromatography stability than nanoflow LC-SRM.

scholarly journals From omics to systems biology: Exploring the mystery box of microbial life

2011 ◽  
Vol 32 (4) ◽  
pp. 147
Author(s):  
Martin Ostrowski ◽  
Sasha Tetu ◽  
Karl Hassan ◽  
Anahit Penesyan ◽  
Kent Lim ◽  
...  
Keyword(s):  
Experimental Data ◽  
Systems Biology ◽  
Molecular Biology ◽  
High Throughput ◽  
Individual Gene ◽  
Microbial Life

Microbial molecular biology has traditionally used very reductionist approaches; for example, find a gene of interest, clone it or knock it out and see if you can detect a phenotype. The genomics era has opened up the possibility of analysing microbes and communities at a systems level by combining high-throughput experimental data from genomic, transcriptomic, proteomic and phenomic techniques. This parallels earlier reductionist approaches by going from DNA to RNA to protein to phenotype, albeit on a global rather than individual gene scale.

0306 Exploring the feasibility of using copy number variants as genetic markers through large-scale whole genome sequencing experiments

2016 ◽  
Vol 94 (suppl_5) ◽  
pp. 146-146
Author(s):  
D. M. Bickhart ◽  
L. Xu ◽  
J. L. Hutchison ◽  
J. B. Cole ◽  
D. J. Null ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genetic Markers ◽  
Genome Sequencing ◽  
Copy Number ◽  
Large Scale ◽  
Copy Number Variants ◽  
Whole Genome

Accelerated Discovery of High-Refractive-Index Polyimides via First-Principles Molecular Modeling, Virtual High-Throughput Screening, and Data Mining

2019 ◽  
Author(s):  
Mohammad Atif Faiz Afzal ◽  
Mojtaba Haghighatlari ◽  
Sai Prasad Ganesh ◽  
Chong Cheng ◽  
Johannes Hachmann
Keyword(s):  
Data Mining ◽  
Refractive Index ◽  
High Throughput ◽  
First Principles ◽  
High Throughput Screening ◽  
Large Scale ◽  
Computational Study ◽  
High Refractive Index ◽  
Structural Features ◽  
Learning Program

<div>We present a high-throughput computational study to identify novel polyimides (PIs) with exceptional refractive index (RI) values for use as optic or optoelectronic materials. Our study utilizes an RI prediction protocol based on a combination of first-principles and data modeling developed in previous work, which we employ on a large-scale PI candidate library generated with the ChemLG code. We deploy the virtual screening software ChemHTPS to automate the assessment of this extensive pool of PI structures in order to determine the performance potential of each candidate. This rapid and efficient approach yields a number of highly promising leads compounds. Using the data mining and machine learning program package ChemML, we analyze the top candidates with respect to prevalent structural features and feature combinations that distinguish them from less promising ones. In particular, we explore the utility of various strategies that introduce highly polarizable moieties into the PI backbone to increase its RI yield. The derived insights provide a foundation for rational and targeted design that goes beyond traditional trial-and-error searches.</div>

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