five

Data from: Microevolution of S-allele frequencies in wild cherry populations: respective impacts of negative frequency dependent selection and genetic drift|遗传进化数据集|植物生物学数据集

收藏
DataONE2011-07-12 更新2024-06-27 收录
遗传进化
植物生物学
下载链接:
https://search.dataone.org/view/null
下载链接
链接失效反馈
资源简介:
Negative frequency dependent selection (NFDS) is supposed to be the main force controlling allele evolution at the gametophytic self-incompatibility locus (S-locus) in strictly outcrossing species. Genetic drift also influences S-allele evolution. In perennial sessile organisms, evolution of allelic frequencies over two generations is mainly shaped by individual fecundities and spatial processes. Using wild cherry populations between two successive generations, we tested whether S-alleles evolved following NFDS qualitative and quantitative predictions. We showed that allelic variation was negatively correlated with parental allelic frequency as expected under NFDS. However, NFDS predictions in finite population failed to predict more than half all S-allele quantitative evolution. We developed a spatially-explicit mating model which included the S-locus. We studied the effects of self-incompatibility and local drift within populations due to pollen dispersal in spatially distributed individuals, and variation in male fecundity on male mating success and allelic frequency evolution. Male mating success was negatively related to male allelic frequency as expected under NFDS. Spatial genetic structure combined with self-incompatibility resulted in higher effective pollen dispersal. Limited pollen dispersal in structured distributions of individuals and genotypes, non-random distribution of individuals and unequal pollen production significantly contributed to S-allele frequency evolution by creating local drift effects strong enough to counteract the NFDS effect on some alleles.
创建时间:
2011-07-12
用户留言
有没有相关的论文或文献参考?
这个数据集是基于什么背景创建的?
数据集的作者是谁?
能帮我联系到这个数据集的作者吗?
这个数据集如何下载?
点击留言
数据主题
具身智能
数据集  4098个
机构  8个
大模型
数据集  439个
机构  10个
无人机
数据集  37个
机构  6个
指令微调
数据集  36个
机构  6个
蛋白质结构
数据集  50个
机构  8个
空间智能
数据集  21个
机构  5个
5,000+
优质数据集
54 个
任务类型
进入经典数据集
热门数据集

Google Scholar

Google Scholar是一个学术搜索引擎,旨在检索学术文献、论文、书籍、摘要和文章等。它涵盖了广泛的学科领域,包括自然科学、社会科学、艺术和人文学科。用户可以通过关键词搜索、作者姓名、出版物名称等方式查找相关学术资源。

scholar.google.com 收录

CatMeows

该数据集包含440个声音样本,由21只属于两个品种(缅因州库恩猫和欧洲短毛猫)的猫在三种不同情境下发出的喵声组成。这些情境包括刷毛、在陌生环境中隔离和等待食物。每个声音文件都遵循特定的命名约定,包含猫的唯一ID、品种、性别、猫主人的唯一ID、录音场次和发声计数。此外,还有一个额外的zip文件,包含被排除的录音(非喵声)和未剪辑的连续发声序列。

huggingface 收录

DALY

DALY数据集包含了全球疾病负担研究(Global Burden of Disease Study)中的伤残调整生命年(Disability-Adjusted Life Years, DALYs)数据。该数据集提供了不同国家和地区在不同年份的DALYs指标,用于衡量因疾病、伤害和早逝导致的健康损失。

ghdx.healthdata.org 收录

Canadian Census

**Overview** The data package provides demographics for Canadian population groups according to multiple location categories: Forward Sortation Areas (FSAs), Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs), Federal Electoral Districts (FEDs), Health Regions (HRs) and provinces. **Description** The data are available through the Canadian Census and the National Household Survey (NHS), separated or combined. The main demographic indicators provided for the population groups, stratified not only by location but also for the majority by demographical and socioeconomic characteristics, are population number, females and males, usual residents and private dwellings. The primary use of the data at the Health Region level is for health surveillance and population health research. Federal and provincial departments of health and human resources, social service agencies, and other types of government agencies use the information to monitor, plan, implement and evaluate programs to improve the health of Canadians and the efficiency of health services. Researchers from various fields use the information to conduct research to improve health. Non-profit health organizations and the media use the health region data to raise awareness about health, an issue of concern to all Canadians. The Census population counts for a particular geographic area representing the number of Canadians whose usual place of residence is in that area, regardless of where they happened to be on Census Day. Also included are any Canadians who were staying in that area on Census Day and who had no usual place of residence elsewhere in Canada, as well as those considered to be 'non-permanent residents'. National Household Survey (NHS) provides demographic data for various levels of geography, including provinces and territories, census metropolitan areas/census agglomerations, census divisions, census subdivisions, census tracts, federal electoral districts and health regions. In order to provide a comprehensive overview of an area, this product presents data from both the NHS and the Census. NHS data topics include immigration and ethnocultural diversity; aboriginal peoples; education and labor; mobility and migration; language of work; income and housing. 2011 Census data topics include population and dwelling counts; age and sex; families, households and marital status; structural type of dwelling and collectives; and language. The data are collected for private dwellings occupied by usual residents. A private dwelling is a dwelling in which a person or a group of persons permanently reside. Information for the National Household Survey does not include information for collective dwellings. Collective dwellings are dwellings used for commercial, institutional or communal purposes, such as a hotel, a hospital or a work camp. **Benefits** - Useful for canada public health stakeholders, for public health specialist or specialized public and other interested parties. for health surveillance and population health research. for monitoring, planning, implementation and evaluation of health-related programs. media agencies may use the health regions data to raise awareness about health, an issue of concern to all canadians. giving the addition of longitude and latitude in some of the datasets the data can be useful to transpose the values into geographical representations. the fields descriptions along with the dataset description are useful for the user to quickly understand the data and the dataset. **License Information** The use of John Snow Labs datasets is free for personal and research purposes. For commercial use please subscribe to the [Data Library](https://www.johnsnowlabs.com/marketplace/) on John Snow Labs website. The subscription will allow you to use all John Snow Labs datasets and data packages for commercial purposes. **Included Datasets** - [Canadian Population and Dwelling by FSA 2011](https://www.johnsnowlabs.com/marketplace/canadian-population-and-dwelling-by-fsa-2011) - This Canadian Census dataset covers data on population, total private dwellings and private dwellings occupied by usual residents by forward sortation area (FSA). It is enriched with the percentage of the population or dwellings versus the total amount as well as the geographical area, province, and latitude and longitude. The whole Canada's population is marked as 100, referring to 100% for the percentages. - [Detailed Canadian Population Statistics by CMAs and CAs 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-cmas-and-cas-2011) - This dataset covers the population statistics of Canada by Census Metropolitan Areas (CMAs) and Census Agglomerations (CAs). It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by FED 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-fed-2011) - This dataset covers the population statistics of Canada from 2011 by Federal Electoral District of 2013 Representation Order. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by Health Region 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-health-region-2011) - This dataset covers the population statistics of Canada by health region. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. - [Detailed Canadian Population Statistics by Province 2011](https://www.johnsnowlabs.com/marketplace/detailed-canadian-population-statistics-by-province-2011) - This dataset covers the population statistics of Canada by provinces and territories. It is categorized also by citizen/immigration status, ethnic origin, religion, mobility, education, language, work, housing, income etc. There is detailed characteristics categorization within these stated categories that are in 5 layers. **Data Engineering Overview** **We deliver high-quality data** - Each dataset goes through 3 levels of quality review - 2 Manual reviews are done by domain experts - Then, an automated set of 60+ validations enforces every datum matches metadata & defined constraints - Data is normalized into one unified type system - All dates, unites, codes, currencies look the same - All null values are normalized to the same value - All dataset and field names are SQL and Hive compliant - Data and Metadata - Data is available in both CSV and Apache Parquet format, optimized for high read performance on distributed Hadoop, Spark & MPP clusters - Metadata is provided in the open Frictionless Data standard, and its every field is normalized & validated - Data Updates - Data updates support replace-on-update: outdated foreign keys are deprecated, not deleted **Our data is curated and enriched by domain experts** Each dataset is manually curated by our team of doctors, pharmacists, public health & medical billing experts: - Field names, descriptions, and normalized values are chosen by people who actually understand their meaning - Healthcare & life science experts add categories, search keywords, descriptions and more to each dataset - Both manual and automated data enrichment supported for clinical codes, providers, drugs, and geo-locations - The data is always kept up to date – even when the source requires manual effort to get updates - Support for data subscribers is provided directly by the domain experts who curated the data sets - Every data source’s license is manually verified to allow for royalty-free commercial use and redistribution. **Need Help?** If you have questions about our products, contact us at [info@johnsnowlabs.com](mailto:info@johnsnowlabs.com).

Databricks 收录

AQA-7

AQA-7 是一个用于动作质量评估(AQA)的统一基准数据集,旨在通过整合多个领域的数据集来标准化评估方法。该数据集包含视频、骨骼数据和多模态输入,涵盖了体育分析、技能评估和医疗护理等多个应用领域。数据集的创建过程通过系统分析现有文献和实验协议,确保了评估的准确性和计算效率。AQA-7 的应用领域广泛,旨在解决动作质量评估中的偏差问题,提供客观的自动化评估,特别是在体育评分、技能评估和康复训练中具有重要意义。

arXiv 收录