enGenome’s Post

Big News! 🌐 Catch us at Global Bio-India 2023 as we unveil our software tech designed for Next-Generation Sequencing (NGS). 🧬 Be part of the journey to streamline genomics analysis, optimising research processes for greater efficiency. Don't miss out! #GlobalBioIndia2023 #NGSTech #OptimizingGenomics 💻 #heathcare #lifesciences #biotechnology #bioinformatics

SeqWell ExpressPlex NGS library prep automation = super fast QC of your synthetic constructs - join our webinar with SPT Labtechnto find out how #ngs #automation #syntheticbiology

Diving into the future of single-cell data analysis, a recent study introduces groundbreaking strategies for cell type annotation. Leveraging active and self-supervised learning, this research significantly advances the efficiency of annotating single-cell expression data. The incorporation of adaptive reweighting and marker-informed strategies not only enhances performance in imbalanced datasets but also identifies novel cell types, showcasing the power of machine learning in refining biological data interpretation. #SingleCell #MachineLearning #NatureCommunications #Genomics #Bioinformatics 🧬💻🔬

A new methodology, called CellHint, can unify different single-cell data from across the world. 🌍 This tool is freely available worldwide and can create a harmonised dataset for the study of human health and disease. 🔬 #singlecell genomics enables the understanding of every cell in the context of the human body at high resolution. Currently, a challenge in assembling the diverse datasets produced by single-cell research is that there is no unified system for naming and organising data. To address this, researchers from the Wellcome Sanger Institute, and collaborators, developed CellHint, which uses machine learning to unify data produced independently across the world, allowing it to be accessed by the wider research community, potentially driving discoveries. 🔎 To find out more, read the full story here ⤵ https://lnkd.in/ebnjHb5Q #genomics

Come get a demo of our new OhmX platform at ASHG!

Tecan and PacBio Partner to Automate High-Accuracy Long-Read Sequencing 🔬 Long-read sequencing is a powerful tool for understanding genomic variation, but it can be time-consuming and labor-intensive to prepare libraries for sequencing. 😱 Tecan and PacBio are excited to announce a new partnership to automate the library preparation process for high-accuracy long-read sequencing. 🎉 This collaboration combines Tecan's DreamPrep NGS Compact workstation with PacBio's SMRTbell® prep kit 3.0 reagents to create an automated workflow that can produce high-quality libraries with minimal hands-on time. 💯 The automated workflow is designed to improve the reproducibility of long-read sequencing and reduce the cost per sample. 💰 This is a major step forward for the genomics community and will enable researchers to accelerate discovery by making long-read sequencing more accessible and affordable. 🚀 #genomics #sequencing #innovation #collaboration #automation #highthroughputscreening #longread #accuracy #costsavings #research #discovery #invenialifesciences

With advances in #NGS technology, the process of library preparation has become even more of a financial and time constraint to high-throughput sequencing core facilities. In our latest application note, discover how our mosquito® automated liquid handler was successfully used by scientists at the Centre of Genomic Research at the University of Liverpool to miniaturize the preparation of DNA libraries for Illumina sequencing without compromising data quality. By reducing the volumes tenfold from the original protocol, the team have been able to increase throughput whilst benefiting from significant cost savings. https://bit.ly/46hIg9s #genomics #liquidhandling

🎉 I am pleased to share my end-of-year project, “Prediction of Antimicrobial Resistance of Escherichia coli Based on Machine Learning”. This project aims to demonstrate the potential of integrating machine learning into AMR diagnostics while addressing the improvements needed to ensure their reliable application. In our study, we evaluated five machine learning models: Decision Tree (DT), Random Forest (RF), Support Vector Classifier (SVC), k-nearest neighbors (KNN), and Gaussian Naive Bayes (Gaussian NB), optimizing them for best performance in predicting AMR for the antibiotics Ciprofloxacin (CIP) and Cefotaxime (CTX) using whole-genome sequencing data of E. coli. These models were meticulously tested and compared to assess their performance and effectiveness in predicting antimicrobial resistance of E. coli, with the goal of improving diagnosis and treatment strategies. I would like to express my sincere gratitude to my supervisor, Pr. Maher Gtari, for his support and guidance throughout this project, and to Pr. Sami Fattouch, our project examiner, for his insightful feedback and encouragement. Additionally, I would like to thank my committed colleagues, Tasnim Ouesleti and Siwar Khmiri, for their collaboration and support. #MachineLearning #AMR #Resistome #Bioinformatics #Genomics #ArtificialIntelligence

🎯 Struggling with accuracy in variant interpretation? With eVai, precision is non-negotiable. Achieving an impressive 98% variant classification accuracy, our proprietary AI technology meticulously assigns a pathogenicity score to every variant, even VUS. This layer of intelligence beyond ACMG guidelines alone, allows you to concentrate on the most promising variants, elevating the diagnostic process to unprecedented levels of accuracy and reliability. Talk to our experts: https://lnkd.in/dV7Sm6-x #variantanalysis #ngs #bioinformatics #genomics #evai

📣 News Alert! 🚀 The latest enhancements to Alamut™️ Visual Plus, elevating your variant annotation experience to new heights! What's NEW? 🌟 💡 gnomAD v4 Integration: Now available on GRCh38 genome build, 5x larger database. Explore exome data from 730,947 individuals (incl. 416,555 UK Biobank) & genome data from 76,215. 💡 New Coding Consequence Algorithm: Our robust, HGVS-compliant algorithm corrects rare errors ensuring accuracy and reliability in variant annotation. ➡ Click here for a personalized demo: https://loom.ly/DRirc_4 #Alamut #AVP #AlamutVisualPlus #variantinterpretation #variantannotation #genomics #genetics #datadrivenmedicine