数据链接：
官方服务：
资源简介：
SRF-Net is a deep learning model for inversion of surface-wave dispersion and receiver function.
应用场景：
提供机构：
Peking university创建时间：
2023-07-08
相关数据集
ATF6 safeguards organelle homeostasis and cellular aging in human mesenchymal stem cells
Loss of organelle homeostasis is a hallmark of aging. However, it remains elusive how this occurs at transcriptional levels. Here, we report that human mesenchymal stem cell (hMSC) aging is associated
干细胞与再生医学数据中心2022-02-20 更新90
Dispersion Curves for Long Beach
Dispersion curves calculated with frequency-Bessle transform method, and picked with an AI approach DisperNet, for the Long Beach seismic array. There are 5297 dispersion curve files, with each refere
Harvard Dataverse2022-02-02 更新30
Proteomic profiling of WW-24-interacting proteins via affinity pull-down in A549 cell
Proteomic profiling of WW-24-interacting proteins via affinity pull-down in A549 cell
integrated proteome resources10
Stacked multiband receiver functions beneath contiguous U.S. and preferred inverted parameters
The preferred 12 parameters and their uncertainties (Table S2). Grouped and stacked receiver functions from the contiguous U.S. See the readme file for detail format.
NIAID Data Ecosystem30
Forearc on-shore receiver functions, station subsurface models, and fitted slab model for Cascadia (North America)
This data publication contains (i) a slab model of the Cascadia subduction zone, derived from receiver functions, parameterized as depth to the three interfaces: t (top), c (central) and m (Moho), in
DataCite Commons2025-12-10 更新20
