Project description:We performed a zebrafish forward genetic screen by Tol2 mediated gene-trap approach and uncovered one mutant stac (The number of the transgenic line: B55) that showed severe cell-death distributed in the various brain and trunk in the homozygote embryos. Analysis of stac homozygous embryos demonstrates typical apoptosis. So it is necessary to analyze whether the apoptosis and cell cycle regulated signaling transductions are changed in the mutant, in order to provide valuable clues to some other species. And the up-regulated and down-regulated genes in the mutant compared to the WT were examined by zebrafish cDNA microarray.
Project description:In order to more accurately discover the cause of drug resistance in tumor treatment, and to provide a new basis for precise treatment.
Therefore, based on the umbrella theory of precision medicine, we carried out this single-center, prospective, and observational study to include patients with liver metastases from colorectal cancer. By combining genome, transcriptome, and proteomic sequencing data, we established a basis for colorectal cancer liver Transfer the multi-omics data of the sample, describe the reason for the resistance of the first-line treatment, and search for new therapeutic targets.
Project description:Quantitative mass spectrometry has transformed proteomics by allowing the simultaneous quantification of thousands of proteins. To boost statistical power, it is necessary to increase sample sizes by combining patient-derived data from various institutions. However, this practice raises significant privacy concerns. We created a DIA-LFQ dataset containing 118 samples generated from Escherichia coli MG1655 (DSM 18039) cultures and distributed them to five independent proteomics centers. This distributed data were used as a proof of concept to introduce FedProt - the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data.
Project description:Quantitative mass spectrometry has transformed proteomics by allowing the simultaneous quantification of thousands of proteins. To boost statistical power, it is necessary to increase sample sizes by combining patient-derived data from various institutions. However, this practice raises significant privacy concerns. We created this dataset comtaining 30 healthy donors and 30 patients suffering from focal segmental glomerulosclerosis - a rare kidney disease - and distributed them to three independent proteomics centers. This distributed data were used as a proof of concept to introduce FedProt - the first privacy-preserving tool for collaborative differential protein abundance analysis of distributed data.
