Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
Project description:To explore the correlation between gene mutations of metastatic colorectal cancer and TCM syndrome types based on Second-generation sequencing technology.
Project description:The project will use exome sequencing to search for genetic predispositions for familial colorectal cancer (CRC). Except for certain syndromes there is today no good method for identifying individuals with a hereditary high risk for CRC (about 25% of the cases). There is currently no routine screening of the population in Norway for CRC today. Coloscopy, which is the most reliable method, is demanding with respect to resources, it can be painful, and may have complications. This project will attempt to find genetic determinants for identification of individuals with increased risk for familial CRC. Such methods will reduce unnecessary medical examination of unaffected family members, and will make it easier to focus health services on individuals with increased risk. This will represent a significant contribution towards improved health reduced death rate caused by CRC. The project includes research on the ethical aspects, in particular challenges related to how feedback to donors is handled.
Project description:Subsequently, using a combination of BSA-seq, transcriptomic sequencing (RNA-seq), and proteomic sequencing approaches, we identified the candidate gene Nitab4.5_0008674g0010 that encodes dihydroneopterin aldolase as a factor associated with tobacco leaf yellowing.
Project description:De novo sequencing and expression of recombinant 1D3 antibody (R1D3). To achieve maximum coverage for antibody sequencing, 5 µg of the antibody original 1D3 was digested in parallel with five different proteases: trypsin, elastase, chymotrypsin, and Asp-N. For each digestion mixture, peptides were loaded onto a nanoflow C18 HPLC column, and peptides were resolved using an aqueous to organic gradient over the course of 90 minutes. As they eluted from the column, peptides were directly ionized on a Thermo Fisher Orbitrap orbitrap Velos mass spectrometer. In a data-dependent manner, both high-resolution full mass measurements and multiple different tandem mass fragmentation (MS/MS) modalities were collected to give the greatest likelihood of correct sequence interpretation. These include standard collision-induced dissociation (CID), higher-energy dissociation (HCD), and electron transfer dissociation (ETD).
After acquisition, data were transferred to Abterra Bioscience for analysis using their proprietary Valens platform. Briefly, an analysis of bottom-up mass spectra generated by the Vanderbilt University Proteomics facility using multiple enzymes was conducted. The framework sequence was identified by performing a database search of the spectra against the germline immunoglobulin gene sequences.