five

Data from: Population structure of mountain pine beetle symbiont Leptographium longiclavatum and the implication on the multipartite beetle-fungi relationships|生态学数据集|真菌学数据集

收藏
DataONE2021-11-29 更新2024-06-08 收录
生态学
真菌学
下载链接:
https://search.dataone.org/view/sha256:db4c5eba1173eb14fe9d6de35984cad4f0d9552568f7f981dc5e0d8e680754dc
下载链接
链接失效反馈
资源简介:
AbstractOver 18 million ha of forests have been destroyed in the past decade in Canada by the mountain pine beetle (MPB) and its fungal symbionts. Understanding their population dynamics is critical to improving modeling of beetle epidemics and providing potential clues to predict population expansion. Leptographium longiclavatum and Grosmannia clavigera are fungal symbionts of MPB that aid the beetle to colonize and kill their pine hosts. We investigated the genetic structure and demographic expansion of L. longiclavatum in populations established within the historic distribution range and in the newly colonized regions. We identified three genetic clusters/populations that coincide with independent geographic locations. The genetic profiles of the recently established populations in northern British Columbia (BC) and Alberta suggest that they originated from central and southern BC. Approximate Bayesian Computation supports the scenario that this recent expansion represents an admixture of individuals originating from BC and the Rocky Mountains. Highly significant correlations were found among genetic distance matrices of L. longiclavatum, G. clavigera, and MPB. This highlights the concordance of demographic processes in these interacting organisms sharing a highly specialized niche and supports the hypothesis of long-term multipartite beetle-fungus co-evolutionary history and mutualistic relationships., Usage notesLL_suppTable1Microsatellite profiles of 10 loci for 241 Leptographium longiclavatum isolates (isolates in grey are clones). First column is the name of the isolates, and the second represents the location.
创建时间:
2024-03-16
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

flames-and-smoke-datasets

该仓库总结了多个公开的火焰和烟雾数据集,包括DFS、D-Fire dataset、FASDD、FLAME、BoWFire、VisiFire、fire-smoke-detect-yolov4、Forest Fire等数据集。每个数据集都有详细的描述,包括数据来源、图像数量、标注信息等。

github 收录

Materials Project 在线材料数据库

Materials Project 是一个由伯克利加州大学和劳伦斯伯克利国家实验室于 2011 年共同发起的大型开放式在线材料数据库。这个项目的目标是利用高通量第一性原理计算,为超过百万种无机材料提供全面的性能数据、结构信息和计算模拟结果,以此加速新材料的发现和创新过程。数据库中的数据不仅包括晶体结构和能量特性,还涵盖了电子结构和热力学性质等详尽信息,为研究人员提供了丰富的材料数据资源。相关论文成果为「Commentary: The Materials Project: A materials genome approach to accelerating materials innovation」。

超神经 收录

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

TCIA

TCIA(The Cancer Imaging Archive)是一个公开的癌症影像数据集,包含多种癌症类型的医学影像数据,如CT、MRI、PET等。这些数据通常与临床和病理信息相结合,用于癌症研究和临床试验。

www.cancerimagingarchive.net 收录

开源PHM数据集

本文分享了一个全球各大学、研究机构和公司捐赠的PHM(Prognostics and Health Management)开源数据集,涵盖加工制造、轨道交通、能源电力和半导体等行业的多种场景,包含部件级、设备级和产线级数据。用户可以利用这些数据开发智能分析和建模算法,数据集分类包括故障诊断、健康评估和寿命预测。

github 收录