scholarly journals Human Ageing Genomic Resources: 2018 Update

2017 ◽  
Author(s):  
Robi Tacutu ◽  
Daniel Thornton ◽  
Emily Johnson ◽  
Arie Budovsky ◽  
Diogo Barardo ◽  
...  
Keyword(s):  
Association Studies ◽  
Genetic Association Studies ◽  
Quality Data ◽  
Model Organisms ◽  
High Quality Data ◽  
External Resources ◽  
Genomic Resources ◽  
Online Resource ◽  
Human Ageing ◽  
Cross Links

AbstractIn spite of a growing body of research and data, human ageing remains a poorly understood process. To facilitate studies of ageing, over 10 years ago we developed the Human Ageing Genomic Resources (HAGR), which are now the leading online resource for biogerontologists. In this update, we present HAGR’s main functionalities, including new additions and improvements to HAGR. HAGR consists of five databases: 1) the GenAge database of ageing-related genes, in turn composed of a dataset of >300 human ageing-related genes and a dataset with >2000 genes associated with ageing or longevity in model organisms; 2) the AnAge database of animal ageing and longevity, featuring >4000 species; 3) the GenDR database with >200 genes associated with the life-extending effects of dietary restriction; 4) the LongevityMap database of human genetic association studies of longevity with >500 entries; 5) the DrugAge database with >400 ageing or longevity-associated drugs or compounds; 6) the CellAge database with >200 genes associated with cell senescence. All our databases are manually curated by experts to ensure a high quality data and presented in an intuitive and clear interface that includes cross-links across our databases and to external resources. HAGR is freely available online (http://genomics.senescence.info/).

scholarly journals Genetics and genomics of human ageing

2011 ◽  
Vol 366 (1561) ◽  
pp. 43-50 ◽  
Author(s):  
Heather E. Wheeler ◽  
Stuart K. Kim
Keyword(s):  
Human Genetics ◽  
Association Studies ◽  
Transcriptional Profiling ◽  
Genetic Association Studies ◽  
Human Kidney ◽  
Age Related ◽  
Quantitative Trait Mapping ◽  
Human Ageing ◽  
Probability Of Death ◽  
Genomic Convergence

Ageing in humans is typified by the decline of physiological functions in various organs and tissues leading to an increased probability of death. Some individuals delay, escape or survive much of this age-related decline and live past age 100. Studies comparing centenarians to average-aged individuals have found polymorphisms in genes that are associated with long life, including APOE and FOXOA3 , which have been replicated many times. However, the associations found in humans account for small percentages of the variance in lifespan and many other gene associations have not been replicated in additional populations. Therefore, ageing is probably a highly polygenic trait. In humans, it is important to also consider differences in age-related decline that occur within and among tissues. Longitudinal data of age-related traits can be used in association studies to test for polymorphisms that predict how an individual will change over time. Transcriptional and genetic association studies of different tissues have revealed common and unique pathways involved in human ageing. Genomic convergence is a method that combines multiple types of functional genomic information such as transcriptional profiling, expression quantitative trait mapping and gene association. The genomic convergence approach has been used to implicate the gene MMP20 in human kidney ageing. New human genetics technologies are continually in development and may lead to additional breakthroughs in human ageing in the near future.

scholarly journals The endophenotype concept in psychiatric genetics

2006 ◽  
Vol 37 (2) ◽  
pp. 163-180 ◽  
Author(s):  
JONATHAN FLINT ◽  
MARCUS R. MUNAFÒ
Keyword(s):  
Genetic Architecture ◽  
Genetic Basis ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Genetic Effect ◽  
Analytical Techniques ◽  
Effect Sizes ◽  
Model Organisms ◽  
Psychiatric Disease ◽  
Diagnostic Categories

The idea that some phenotypes bear a closer relationship to the biological processes that give rise to psychiatric illness than diagnostic categories has attracted considerable interest. Much effort has been devoted to finding such endophenotypes, partly because it is believed that the genetic basis of endophenotypes will be easier to analyse than that of psychiatric disease. This belief depends in part on the assumption that the effect sizes of genetic loci contributing to endophenotypes are larger than those contributing to disease susceptibility, hence increasing the chance that genetic linkage and association tests will detect them. We examine this assumption by applying meta-analytical techniques to genetic association studies of endophenotypes. We find that the genetic effect sizes of the loci examined to date are no larger than those reported for other phenotypes. A review of the genetic architecture of traits in model organisms also provides no support for the view that the effect sizes of loci contributing to phenotypes closer to the biological basis of disease is any larger than those contributing to disease itself. While endophenotype measures may afford greater reliability, it should not be assumed that they will also demonstrate simpler genetic architecture.

scholarly journals Spliceator: multi-species splice site prediction using convolutional neural networks

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Nicolas Scalzitti ◽  
Arnaud Kress ◽  
Romain Orhand ◽  
Thomas Weber ◽  
Luc Moulinier ◽  
...  
Keyword(s):  
Deep Learning ◽  
High Accuracy ◽  
Quality Data ◽  
Model Organisms ◽  
Splice Sites ◽  
High Quality Data ◽  
Splice Site Prediction ◽  
Ab Initio Prediction ◽  
Wide Range ◽  
Gene Structures

Abstract Background Ab initio prediction of splice sites is an essential step in eukaryotic genome annotation. Recent predictors have exploited Deep Learning algorithms and reliable gene structures from model organisms. However, Deep Learning methods for non-model organisms are lacking. Results We developed Spliceator to predict splice sites in a wide range of species, including model and non-model organisms. Spliceator uses a convolutional neural network and is trained on carefully validated data from over 100 organisms. We show that Spliceator achieves consistently high accuracy (89–92%) compared to existing methods on independent benchmarks from human, fish, fly, worm, plant and protist organisms. Conclusions Spliceator is a new Deep Learning method trained on high-quality data, which can be used to predict splice sites in diverse organisms, ranging from human to protists, with consistently high accuracy.

What Can Digitization Do For Formulated Product Innovation and Development

2020 ◽  
Author(s):  
James McDonagh ◽  
William Swope ◽  
Richard L. Anderson ◽  
Michael Johnston ◽  
David J. Bray
Keyword(s):  
High Performance ◽  
Quality Data ◽  
High Quality Data ◽  
Base Level ◽  
Hybrid Approaches ◽  
Digital Ecosystem ◽  
Recent Developments ◽  
Chemical Simulation ◽  
High Level ◽  
Physical And Chemical

Digitization offers significant opportunities for the formulated product industry to transform the way it works and develop new methods of business. R&D is one area of operation that is challenging to take advantage of these technologies due to its high level of domain specialisation and creativity but the benefits could be significant. Recent developments of base level technologies such as artificial intelligence (AI)/machine learning (ML), robotics and high performance computing (HPC), to name a few, present disruptive and transformative technologies which could offer new insights, discovery methods and enhanced chemical control when combined in a digital ecosystem of connectivity, distributive services and decentralisation. At the fundamental level, research in these technologies has shown that new physical and chemical insights can be gained, which in turn can augment experimental R&D approaches through physics-based chemical simulation, data driven models and hybrid approaches. In all of these cases, high quality data is required to build and validate models in addition to the skills and expertise to exploit such methods. In this article we give an overview of some of the digital technology demonstrators we have developed for formulated product R&D. We discuss the challenges in building and deploying these demonstrators.<br>

Collecting High-Quality Data

2018 ◽  
Author(s):  
Mary Kay Gugerty ◽  
Dean Karlan
Keyword(s):  
Data Collection ◽  
Social Desirability ◽  
Measurement Errors ◽  
Monitoring And Evaluation ◽  
Quality Data ◽  
Social Desirability Bias ◽  
High Quality ◽  
High Quality Data ◽  
Evaluation Systems ◽  
Demand Effect

Without high-quality data, even the best-designed monitoring and evaluation systems will collapse. Chapter 7 introduces some the basics of collecting high-quality data and discusses how to address challenges that frequently arise. High-quality data must be clearly defined and have an indicator that validly and reliably measures the intended concept. The chapter then explains how to avoid common biases and measurement errors like anchoring, social desirability bias, the experimenter demand effect, unclear wording, long recall periods, and translation context. It then guides organizations on how to find indicators, test data collection instruments, manage surveys, and train staff appropriately for data collection and entry.

scholarly journals Case–Parent Trio Studies in Cleft Lip and Palate

2020 ◽  
Vol 07 (03) ◽  
pp. 075-079
Author(s):  
Mahamad Irfanulla Khan ◽  
Prashanth CS
Keyword(s):  
Genetic Variants ◽  
Cleft Lip ◽  
Cleft Lip And Palate ◽  
Association Studies ◽  
Geographical Location ◽  
Genetic Association Studies ◽  
Population Based ◽  
Genome Wide Association Studies ◽  
Family Based ◽  
Study Designs

AbstractCleft lip with or without cleft palate (CL/P) is one of the most common congenital malformations in humans involving various genetic and environmental risk factors. The prevalence of CL/P varies according to geographical location, ethnicity, race, gender, and socioeconomic status, affecting approximately 1 in 800 live births worldwide. Genetic studies aim to understand the mechanisms contributory to a phenotype by measuring the association between genetic variants and also between genetic variants and phenotype population. Genome-wide association studies are standard tools used to discover genetic loci related to a trait of interest. Genetic association studies are generally divided into two main design types: population-based studies and family-based studies. The epidemiological population-based studies comprise unrelated individuals that directly compare the frequency of genetic variants between (usually independent) cases and controls. The alternative to population-based studies (case–control designs) includes various family-based study designs that comprise related individuals. An example of such a study is a case–parent trio design study, which is commonly employed in genetics to identify the variants underlying complex human disease where transmission of alleles from parents to offspring is studied. This article describes the fundamentals of case–parent trio study, trio design and its significances, statistical methods, and limitations of the trio studies.

scholarly journals Velocity Analysis Using Separated Diffractions for Lunar Penetrating Radar Obtained by Yutu-2 Rover

2021 ◽  
Vol 13 (7) ◽  
pp. 1387
Author(s):  
Chao Li ◽  
Jinhai Zhang
Keyword(s):  
Dielectric Permittivity ◽  
Lunar Regolith ◽  
Velocity Model ◽  
Velocity Estimation ◽  
Quality Data ◽  
High Quality Data ◽  
Shallow Subsurface ◽  
Subsurface Structures ◽  
Ground Penetrating ◽  
Permittivity Model

The high-frequency channel of lunar penetrating radar (LPR) onboard Yutu-2 rover successfully collected high quality data on the far side of the Moon, which provide a chance for us to detect the shallow subsurface structures and thickness of lunar regolith. However, traditional methods cannot obtain reliable dielectric permittivity model, especially in the presence of high mix between diffractions and reflections, which is essential for understanding and interpreting the composition of lunar subsurface materials. In this paper, we introduce an effective method to construct a reliable velocity model by separating diffractions from reflections and perform focusing analysis using separated diffractions. We first used the plane-wave destruction method to extract weak-energy diffractions interfered by strong reflections, and the LPR data are separated into two parts: diffractions and reflections. Then, we construct a macro-velocity model of lunar subsurface by focusing analysis on separated diffractions. Both the synthetic ground penetrating radar (GPR) and LPR data shows that the migration results of separated reflections have much clearer subsurface structures, compared with the migration results of un-separated data. Our results produce accurate velocity estimation, which is vital for high-precision migration; additionally, the accurate velocity estimation directly provides solid constraints on the dielectric permittivity at different depth.

scholarly journals Redistribution Preferences, Inequality Information, and Partisan Motivated Reasoning in the United States

Societies ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 65
Author(s):  
Clem Brooks ◽  
Elijah Harter
Keyword(s):  
Party Identification ◽  
Motivated Reasoning ◽  
The United States ◽  
Quality Data ◽  
Historical Time ◽  
High Quality Data ◽  
Redistributive Policies ◽  
Election Studies ◽  
New Evidence ◽  
The U.S

In an era of rising inequality, the U.S. public’s relatively modest support for redistributive policies has been a puzzle for scholars. Deepening the paradox is recent evidence that presenting information about inequality increases subjects’ support for redistributive policies by only a small amount. What explains inequality information’s limited effects? We extend partisan motivated reasoning scholarship to investigate whether political party identification confounds individuals’ processing of inequality information. Our study considers a much larger number of redistribution preference measures (12) than past scholarship. We offer a second novelty by bringing the dimension of historical time into hypothesis testing. Analyzing high-quality data from four American National Election Studies surveys, we find new evidence that partisanship confounds the interrelationship of inequality information and redistribution preferences. Further, our analyses find the effects of partisanship on redistribution preferences grew in magnitude from 2004 through 2016. We discuss implications for scholarship on information, motivated reasoning, and attitudes towards redistribution.

scholarly journals Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kevin K. Esoh ◽  
Tobias O. Apinjoh ◽  
Steven G. Nyanjom ◽  
Ambroise Wonkam ◽  
Emile R. Chimusa ◽  
...  
Keyword(s):  
Genetic Structure ◽  
Ethnic Groups ◽  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Genomic Region ◽  
Sub Saharan Africa ◽  
Genome Wide Association Studies ◽  
Fine Scale ◽  
Sub Saharan

AbstractInferences from genetic association studies rely largely on the definition and description of the underlying populations that highlight their genetic similarities and differences. The clustering of human populations into subgroups (population structure) can significantly confound disease associations. This study investigated the fine-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fine-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi-Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric differentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confirming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in the HBB gene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fine-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.

Sign in / Sign up

Export Citation Format

Share Document