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  • This data accompanies the paper "mTOR Inhibition Restores Amino Acid Balance in Cells Dependent on Catabolism of Extracellular Protein" published in Mol Cell, 2017.
    Data Types:
    • Dataset
    • File Set
  • Data related to the publication: "A Map of Human Type 1 Diabetes Progression by Imaging Mass Cytometry". Damond N, Engler S, Zanotelli VRT, Schapiro D, Wasserfall CH, Kusmartseva I, Nick HS, Thorel F, Herrera PL, Atkinson MA and Bodenmiller B. Cell Metab. 2019 Mar 5;29(3):755-768.e5. https://doi.org/10.1016/j.cmet.2018.11.014 We used imaging mass cytometry to simultaneously image 37 biomarkers with single-cell and spatial resolution in pancreas sections from 12 human donors at different stages of type 1 diabetes. CODE: - Python script for coordinate transformation - Functions for custom histoCAT neighborhood analysis DATA: - Single-cell data - Islet-level data - Cell type information - Cell relationships (cell-cell neighborhoods and cell-islet relationships) - Donors and image metadata. - Subset containing the data for 100 images from 3 donors IMAGES: - Image stacks (37 channels) for all donors (one .7z file per donor, numbers indicate nPOD case IDs) - Cell masks - Panel file with information related to antibodies and metal tags - Metadata file linking donor information to images - Metadata file linking image stack slices and panel information - Subset containing 100 images from 3 donors
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • File Set
  • Data Types:
    • Other
    • Dataset
  • Supplementary Dataset File S1: The proteins identified and quantified by proteomic analysis. Supplementary Dataset File S2: The proteins information by DAVID and STRING analyses. Supplementary Information File S3: The cancer-promotion role of HADHA knockdown in 786-O cell. Supplementary Information File S4: The anti-cancer effect of HADHA overexpression in A498 cell. Supplementary Information File S5: HADHA downregulation in a VHL/HIF-2α-independent manner in 786-O and A498 cells.
    Data Types:
    • Tabular Data
    • Dataset
    • Document
  • Raw data from Headley et al. 2019.
    Data Types:
    • Video
    • Dataset
    • Document
  • The increasingly competitive biopharmaceutical industry requires companies to focus on rapid and low-cost cell line development. Single-cell cloning (SCC) is a critical and high value process for cell line development, and typically problematic because single cell proliferates slowly when cultivated at low cell densities. Conditioned media (CM) provide autocrine growth factors to facilitate single cell proliferation, thus improve SCC efficiency. However, conditioned media (CM) are not a feasible solution for industrial cell line development due to variation and cross contamination concerns. Here, we have found an improvement in the SCC efficiency similar to CM when soy hydrolysate was supplemented in SCC media. Therefore, we concluded that hydrolysate can mimic the autocrine growth factor(s) effect to improve cloning efficiency observed in CM.
    Data Types:
    • Image
    • Dataset
  • figure legend for discription the large anmial model
    Data Types:
    • Image
    • Dataset
  • this dataset include the process data from in vivo and in vitro studies.
    Data Types:
    • Tabular Data
    • Dataset
  • This repository contains the R code used in our analysis of the Lenz et al (NEJM 2008) dataset. The processed data and metadata are available, to allow reproduction of the figures of the present publication. All details and references for these analyses are available in the method section of our manuscript.
    Data Types:
    • Software/Code
    • Tabular Data
    • Dataset
    • Document
    • Text
  • crAss-phage MCP HMM-profiles and Microviridae HMM-profiles
    Data Types:
    • Dataset
    • File Set