Stephen Floor’s Post

 bioinformatician 

🔬 CellBridge: A New Single Cell Workflow 🔬 CellBridge is an automated workflow designed to streamline single-cell RNA sequencing (scRNA-seq) data analysis. It eliminates the need for specialized computational expertise, integrating advanced computational methods to simplify the standard procedures in scRNA-seq data analysis. Check out the full article in the Bioinformatics journal: https://lnkd.in/dd2mCQ_g 🌐 Key Features: ℹ️ Comprehensive end-to-end ecosystem, from raw unaligned sequencing reads to cell type annotation. ℹ️ Inclusive of an informative HTML summary report. ℹ️ Docker-based workflow with functions in R and Python. ℹ️ Covers essential steps like quality control, doublet removal, normalization, batch correction, dimensionality reduction, clustering, and cell-type annotation. 👩💻👨🔬 For Biologists and Bioinformaticians: This tool is a game-changer, offering a user-friendly interface that caters to both biologists and bioinformaticians. Whether you're in academia or leading a team in pharma, CellBridge has the potential of significantly enhancing your research capabilities. 📢 Join the Conversation 📢  Share your thoughts, methods, and tools for single cell clustering in the comments 👇 💬 #CellBridge #SingleCellAnalysis #Bioinformatics #Biotechnology #PharmaInnovation #RNASequencing #DataAnalysis

📢 I’m back with a brand-new tutorial series on my blog and YouTube channel This time I am focussing on the end-to-end bulk RNA-Seq data analysis workflow from raw data processing to advanced analysis. Whether you’re bioinformatics curious, a beginner in the field, or looking to brush up on your skills, this series is tailored to demystify RNA sequencing data analysis 🧬💻 What's in store? - Comprehensive guide to setting up your bioinformatics environment - Detailed how to guide for executing the nf-core/rnaseq pipeline - Walkthroughs from processing FASTQ files to gene set enrichment analyses - Practical insights into quality control and differential expression testing Today's post starts with the basics of raw data analysis, leveraging the power of nf-core, and navigating through setting up and running bioinformatics pipelines effectively on a high-performance computing cluster (HPC) 📝 Read the blog post here: https://lnkd.in/gkyw8wR7 📺 Watch the first video here: https://lnkd.in/gVnZ3_Vr I hope you enjoy and I will catch you all again soon for the next one ✌️ #RNASeq #Bioinformatics #DataScience #nfcore

🔬 DNA Sequencing with Illumina NGS: Step-by-Step Guide 🔬 Discover the step-by-step process of DNA sequencing using Illumina's Next-Generation Sequencing (NGS) technology! 1. Sample Collection and Preparation Collect Sample: Obtain the biological sample (e.g., blood, saliva, tissue). Extract DNA: Use a DNA extraction kit to isolate DNA. Quantify & Check Quality: Measure DNA concentration and check purity with a spectrophotometer and gel electrophoresis. 2. Library Preparation Fragmentation: Break DNA into smaller pieces using sonication or enzymatic digestion. End Repair: Fix the ends of DNA fragments to be blunt-ended. A-tailing: Add an adenine (A) overhang to DNA fragments. Adapter Ligation: Attach Illumina sequencing adapters to DNA ends. Size Selection: Choose DNA fragments of desired size using magnetic beads. PCR Amplification: Amplify DNA fragments to enrich the library. 3. Library Quality Control Quantification: Measure library concentration with a fluorometer (e.g., Qubit). Size Check: Assess fragment sizes using a bioanalyzer or gel electrophoresis. Quality Check: Ensure the library meets Illumina's requirements. 4. Sequencing Load Library: Place the prepared DNA library onto the Illumina flow cell. Cluster Generation: Amplify DNA fragments on the flow cell to create clusters. Run Sequencing: Perform sequencing-by-synthesis on an Illumina sequencer (e.g., MiSeq, HiSeq, NextSeq). 5. Data Processing Base Calling: Convert raw image data into nucleotide sequences. Quality Control: Assess the quality of sequencing reads. Trimming & Filtering: Remove low-quality bases and adapter sequences from reads. 6. Data Analysis Alignment: Align sequences to a reference genome using alignment software (e.g., BWA, Bowtie2). Variant Calling: Identify genetic variants using variant calling tools (e.g., GATK, FreeBayes). Annotation: Annotate variants to understand their biological significance using tools (e.g., ANNOVAR, VEP). . Stay tuned for more insights into the fascinating world of genetics! 🧬✨ #DNASequencing #IlluminaNGS #Genomics #Science #Biotechnology #Research International Brain Research Organization (IBRO) Society for Neuroscience Youth Neuro Australia YOUTH NEUROSCIENCE ASSOCIATION OF NIGERIA

Excited to share my latest Medium article titled 'Using SVM to Classify DNA Promoters.' In genomics, accurately identifying DNA promoters is essential for understanding how genes work and finding new medical treatments. I discuss how Support Vector Machine (SVM) classifiers are changing this field, explaining their practical uses, effectiveness, and what this means for future research. Let's dive into how machine learning and genomics are coming together to make exciting advances in biotechnology and beyond! #Python #MachineLearning #Genomics #Bioinformatics #DataScience https://lnkd.in/g8tWzhi7

"Absolutely thrilled to see the incredible progress in bioinformatics, especially the integration of deep learning in deciphering complex cell-cell interactions from single-cell RNA sequencing data. 🧬🤖 The synergy between biology and technology is truly fascinating, and it's paving the way for groundbreaking discoveries in the life sciences. Exciting times ahead! 👏 #Bioinformatics #DeepLearning #AI #MachineLearning #LifeSciences"

DeepCCI: a deep learning framework for identifying cell-cell interactions from single-cell RNA sequencing data

RNA design gets a boost! 🚀 Researchers introduce #RiboDiffusion, a novel generative diffusion model that tackles the RNA inverse folding problem by learning to design RNA sequences from 3D backbone structures. This powerful tool outperforms baselines and promises to accelerate RNA design for synthetic biology and therapeutics. Quick Read: https://lnkd.in/gvMnNBkp #bioinformatics #rnadesign #rna #syntheticbiology #ai #machinelearning #sciencenews

🌟 Join Deep Genomics, a revolutionary startup leveraging AI and genome biology to decode RNA biology and transform drug development! Our AI Workbench platform decodes the complexity of RNA biology to find novel targets and mechanisms. We're hiring a (Senior) Research Scientist of Statistical Genetics to analyze large-scale human genetic data and identify potential genetic targets for therapeutics. If you have a PhD in biostatistics, strong programming skills, and a passion for innovation, apply now! #DeepGenomics #DrugDevelopment #AI #GenomeBiology #RNA #ResearchScientist #StatisticalGenetics #GeneticDataAnalysis #Biostatistics #Innovation #JobOpportunity 🔬 Are you a (Senior) Research Scientist in Statistical Genetics? Deep Genomics is seeking a talented individual to analyze large-scale human genetic data and identify potential genetic targets for therapeutics. If you have a PhD in biostatistics, strong programming skills, and a passion for innovation, join our multidisciplinary team at the forefront of AI and genome biology! Apply now and be part of revolutionizing drug development! #DeepGenomics #ResearchScientist #StatisticalGenetics #GeneticDataAnalysis #Biostatistics #AI #GenomeBiology #DrugDevelopment #Innovation #JobOpportunity To stay updated with the latest opportunities at Deep Genomics, follow Yogesh Jadhav and click here: https://ift.tt/UBptxTW #DeepGenomics #JobOpportunities #YogeshJadhav #StayUpdated

🧬 What is NGS? NGS, or Next-Generation Sequencing, is a high-throughput method that has revolutionized genomics by enabling the rapid and cost-effective sequencing of DNA and RNA. It's like having a magnifying glass that reveals the intricate genetic code, unlocking insights into diseases, evolution, and more. 💡 Why NGS Matters NGS has transformed research across fields. From diagnosing genetic disorders to tracking disease outbreaks, its applications are far-reaching. In personalized medicine, NGS helps tailor treatments to individual patients based on their genetic makeup. Don't forget agriculture, forensics, and environmental studies benefit from NGS as well! 📊 Data Deluge NGS generates massive datasets, posing challenges in data storage, analysis, and interpretation. Bioinformatics and computational biology play a crucial role in making sense of this data avalanche, turning raw sequences into meaningful insights. 🌐 Collaboration is Key The NGS community thrives on collaboration. Researchers, bioinformaticians, clinicians, and software developers come together to innovate and address NGS-related challenges. Sharing knowledge and resources is pivotal for progress. 📚 Learning Never Stops As technology evolves, so does NGS. Staying updated with the latest advancements, tools, and best practices is a continuous journey. Webinars, workshops, and online courses are great ways to enhance your NGS expertise. Let's keep this conversation going! 🚀 Whether you're a scientist, student, or just curious about genomics, let's connect and exchange insights on the incredible world of Next-Generation Sequencing. 🌎🧬 #NextGenerationSequencing #GenomicRevolution #ScienceCommunity #Bioinformatics #LifelongLearning