Bversity School of Bioscience’s Post

Do you know of these bioinformatics companies making waves in the biopharma industry? 🌊 Bioinformatics is a field of science that integrates computer technology to analyze biological data to boost healthcare research. 🖥️ The bioinformatics industry has a market value of $16.3 billion at present, and is forecasted to reach nearly $24 billion in five years. 📈 Most biotechs rely on bioinformatics in drug discovery to improve their chances of viable candidates making it to the clinic. 🏥 Check out our latest article on five bioinformatics companies making a difference in the biopharma industry in 2024! 👇 https://lnkd.in/deQ7pvJY #bioinformatics #biopharma #healthcareresearch #drugdiscovery #biotechinnovation #BiotechIndustry #healthcaretech #scientificadvances Synthace | Verge Genomics | VeriSIM Life | Recursion | Twist Bioscience | Illumina | QIAGEN | Thermo Fisher Scientific

Bioinformatics is a field of science that integrates computer technology to analyze biological data, particularly DNA and protein sequences, to advance therapies and boost healthcare research. This article looks at five companies at the top of their bioinformatics game in 2024. #biotech #Healthcare #Bioinformatics #Datadiscovery

🚀 Bioinformatics: Powering the Next Frontier in Biotechnology! 🧬 (Post 6) In today's biotech landscape, bioinformatics is key to transforming how we understand complex biological systems, driving advancements in healthcare, agriculture, and more. 🌱💡 🔑 Why Bioinformatics? As biological data grows in scale and complexity, bioinformatics allows scientists to analyze this data efficiently, leading to breakthroughs in drug discovery, personalized medicine, and precision therapies. 🌟 Key Bioinformatics Techniques Shaping the Future: 🔸 Molecular Docking – This computational method predicts how molecules like drugs interact with target proteins, streamlining the drug discovery process and helping to identify the most effective compounds. 🔸 Homology Modeling – Used to predict the 3D structure of proteins when an experimental structure is unavailable and helps in understanding how mutations affect biological processes. 🔸 Phylogenetic Analysis – This technique helps trace evolutionary relationships among organisms, allowing researchers to study the evolution of species and the spread of infectious diseases. 🔸 Next-Generation Sequencing (NGS) – A high-throughput technology that enables the rapid sequencing of entire genomes or specific genes. 🔸 CRISPR Screening – A revolutionary gene-editing technique that can knock out genes at scale, helping researchers discover new drug targets and understand gene function with unprecedented precision. 🔸 Microarray Analysis – A high-throughput tool that measures gene expression levels across thousands of genes simultaneously, providing critical insights into gene regulation and identifying biomarkers for diseases. 🔸 Metagenomics – This method allows the analysis of genetic material from environmental samples, advancing the study of microbial communities and their roles in health, agriculture, and environmental sustainability. At BioPractify we are dedicated to make accessible for everyone. All the References are taken from Internet, all Copyrights belongs to Owners/Publications💻📊 #Bioinformatics #BiotechInnovation #MolecularDocking #NGS #CRISPR #Proteomics #SkillDevelopment #BioPractify #Metagenomics #MicroarrayAnalysis #PrecisionMedicine

𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 𝐢𝐧 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬 𝐌𝐚𝐫𝐤𝐞𝐭: 𝐒𝐢𝐳𝐞, 𝐒𝐡𝐚𝐫𝐞, 𝐚𝐧𝐝 𝐓𝐫𝐞𝐧𝐝𝐬 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 2024-2033 𝐆𝐞𝐭 𝐅𝐫𝐞𝐞 𝐀𝐜𝐜𝐞𝐬𝐬 𝐭𝐨 𝐃𝐞𝐦𝐨 𝐑𝐞𝐩𝐨𝐫𝐭, 𝐄𝐱𝐜𝐞𝐥 𝐏𝐢𝐯𝐨𝐭 𝐚𝐧𝐝 𝐓𝐨𝐂: https://lnkd.in/dC6sXX5C The #ArtificialIntelligence in #Bioinformatics Market Size was valued at USD 3.97 Mn in 2023 and is predicted to reach USD 125.3 Mn by 2033 at a 42.1% CAGR during the forecast period for 2024-2033. ▪ 𝐊𝐞𝐲 𝐏𝐥𝐚𝐲𝐞𝐫𝐬 𝐂𝐨𝐯𝐞𝐫𝐞𝐝 𝐢𝐧 𝐭𝐡𝐢𝐬 𝐑𝐞𝐩𝐨𝐫𝐭 𝐚𝐫𝐞:  JADBio AutoML Gnosis Data Analysis Fios Genomics SOPHiA GENETICS Biomax DNASTAR Ardigen Source BioScience QIAGEN NeoGenomics Laboratories Eurofins Scientific Finland Oy Illumina Thermo Fisher Scientific Insilico Medicine Strand Life Sciences Dassault Systèmes iNDX.Ai Paige - AI Website Builder SomaLogic #AIinBiotech #MachineLearning #DeepLearning #BioTechTrends #HealthData #AIinResearch

Why #BioinformaticsIndustry to be Privatised? Considering the dynamic nature of bioinformatics, privatization can fuel innovation and efficiency. Private sector involvement often brings substantial investment, fostering R&D for cutting-edge technologies. Competition drives progress, leading to quicker advancements in genomics, personalized medicine, and data analytics. This shift can accelerate breakthroughs, translating into improved healthcare solutions. Collaboration between academia and industry remains crucial, ensuring ethical practices and knowledge sharing. #Bioinformatics #Innovation #HealthTech #PrivateSector #BiotechAdvancements https://lnkd.in/dBBWj79J

Please join the IMAG/MSM WG on Multiscale Modeling and Viral Pandemics and GLIMPRINT, Thursday January 11 at 3:00 PM Eastern time for: Jake Beal, Raytheon BBN Technologies: "Agile Data Curation for Modeling and Design." Investigating complex biological systems requires integrating many different types of information in an iterative process of design and experimentation. In synthetic biology, this has often been enunciated as a “Design-Build-Test-Learn” (DBTL) loop, but the current reality typically falls far from its promise. One key reason for this is the field’s lack of effective established practices for curation, quality control, and integration across designs, experiment plans, metadata, and data. Software engineering has historically had analogous challenges relating to testing, documentation, and integration. Over the past two decades, however, the agile software community has radically transformed professional software development by developing processes that bring management of correctness, completeness, and compatibility into the core activities of software development and supporting them with complementary automation tools. We observe that, with appropriate choices of representation and process controls, the same processes and tools can be directly applied to synthetic biology designs, data, metadata, and models. Early application of this approach have given promising results, we illustrate with three examples: collective development of genetic designs for the iGEM 2022 distribution, model-driven analysis of tunable CRISPR safety switch architectures, and automation-assisted analysis of flow cytometry experiments. Bio: Dr. Jacob Beal is an Engineering Fellow at Raytheon BBN Technologies. His work in synthetic biology includes development of standards for representation and communication of biological designs and experiments, signature-based detection of controlled pathogens, methods for calibrated flow cytometry, precision analysis and design of genetic regulatory networks, and engineering of biological information processing devices. For more information see: https://lnkd.in/g9eaZtdm Register at: https://lnkd.in/env6WVM #IMAGMSM, #MathematicalBiology, #SystemsBiology, #DigitalTwins #Medicine, #ML, #Medicine, #Technology, #Data, #MSMViral, #ComputationalBiology, #IUB, #DataScience, #GLIMPRINT, #SyntheticBiology, #SoftwareEngineering, #DesignTestBuild, #QualityControl, #AgileProgramming, #IGEM, #Biosafety, #Biology, #Bioinformatics, #Automation, #BBN, #Curation, #DataScience

Looking for something to read for friday afternoon or during weekend? Check this BD Rhapsody blog post on our website: https://lnkd.in/gkHhN9KE Interesting post including information of reduced sequencing costs, bioinformatics and applications like: Fragment-seq, FLOUR-Seq! Contact us for more information. #singlecellsequencing #BDRhapsody #Multiomics #longreadsequencing

𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬 𝐯𝐬. 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐁𝐢𝐨𝐥𝐨𝐠𝐲   Bioinformatics and computational biology are closely related fields that often overlap, but they have distinct focuses and methodologies. Here's a comparison to help clarify the differences:    1. 𝐅𝐨𝐜𝐮𝐬 𝐚𝐧𝐝 𝐆𝐨𝐚𝐥𝐬:      - 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬: Primarily concerned with the development of software tools, databases, and algorithms to store, manage, analyze, and visualize biological data, particularly large-scale data such as genomic sequences or proteomic profiles. The focus is often on handling and processing data.      - 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐁𝐢𝐨𝐥𝐨𝐠𝐲: More focused on the development and application of data-analytical and theoretical methods, mathematical modeling, and computational simulation techniques to the study of biological systems. The emphasis is on understanding biological processes.      2. 𝐃𝐚𝐭𝐚 𝐯𝐬. 𝐌𝐨𝐝𝐞𝐥𝐬:      - 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬: Generally deals with the practical issues of handling large datasets—such as sequencing data or protein structures—often aiming to extract useful information or insights from these data through analysis and interpretation.      - 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐁𝐢𝐨𝐥𝐨𝐠𝐲: Involves creating mathematical models or computational simulations to understand biological systems. This field might use data generated through bioinformatics tools, but the main goal is to understand the underlying biological mechanisms.      3. 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧𝐬:      - 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬: Applications include sequence alignment, gene finding, genome assembly, drug design, drug discovery, protein structure alignment and prediction, prediction of gene expression, protein-protein interactions, and the modeling of evolution.      - 𝐂𝐨𝐦𝐩𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐁𝐢𝐨𝐥𝐨𝐠𝐲: Focuses on modeling cellular interactions, ecosystem dynamics, brain function, and other biological processes. It often involves simulating biological systems to study their behavior under various conditions. #bioinformatics #computationalbiology #dataanalysis #modelling

I feel every biotechnology practitioner should laverage power of Bioinformatics in their toolkit. I have prepared the list of tools that each biotech person should learn: 1️⃣ BLAST: Identify sequence similarities to uncover novel genes. 2️⃣ Galaxy: Seamless platform for intuitive analysis workflows and tool integration. 3️⃣ CLUSTAL: Hone your sequence alignment skills for precise genetic comparisons. 4️⃣ PyMOL: Delve into 3D molecular structures for profound structural analysis. 5️⃣ UCSC Genome Browser: Visualize and annotate genomic sequences with precision. 6️⃣ Bioconductor: Leverage R-based software for robust bioinformatics data analysis and visualization. 7️⃣ BEDTools: Efficiently manipulate genomic intervals for diverse analyses. 8️⃣ IGV (Integrative Genomics Viewer): Explore and analyze large-scale genomic datasets. 9️⃣ Trinity: Assemble transcriptomes from RNA-Seq data for comprehensive insights. 🔟 GROMACS: Engage in molecular dynamics simulations for detailed biomolecular studies. Make sure you checkmark all these tools and make use of these tools developed by poeple like us.

𝐀 𝐂𝐨𝐦𝐩𝐫𝐞𝐡𝐞𝐧𝐬𝐢𝐯𝐞 𝐆𝐮𝐢𝐝𝐞 𝐨𝐧 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬 𝐆𝐫𝐚𝐛 𝐓𝐡𝐞 𝐏𝐃𝐅 𝐓𝐨 𝐊𝐧𝐨𝐰 𝐌𝐨𝐫𝐞@ https://lnkd.in/dcwjZUud Bioinformatics is the interdisciplinary field combining biology, computer science, and data analysis to understand biological data, such as genetic sequences, protein structures, and cellular networks. By leveraging algorithms and software, bioinformatics plays a key role in decoding complex biological information. 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬 The rise of personalized medicine, drug discovery, and genomics opens up vast opportunities in bioinformatics. Advancements in machine learning and AI are empowering faster, more precise biological data analysis, enhancing research efficiency, and revolutionizing healthcare. 𝐎𝐩𝐩𝐨𝐫𝐭𝐮𝐧𝐢𝐭𝐢𝐞𝐬 Genomic and proteomic data analysis Drug discovery and development Personalized medicine Biotechnology research Agricultural genomics 𝐄𝐧𝐝 𝐔𝐬𝐞𝐫𝐬 Research institutions Pharmaceutical companies Biotech firms Healthcare providers Agricultural researchers #Bioinformatics #DataScience #PersonalizedMedicine #Genomics #Biotech #HealthcareInnovation #AIinHealthcare #Bioinformatics #DataScience #Genomics #ComputationalBiology #BigData #MachineLearning #BioinformaticsResearch #DataAnalysis #BioinformaticsTools #BioinformaticsCommunity #BioinformaticsCareer #BioinformaticsEducation #BioinformaticsNews #BioinformaticsConference #BioinformaticsTechnology #BioinformaticsJobs #BioinformaticsExperts #BioinformaticsSolutions #BioinformaticsIndustry #BioinformaticsTrends #BioinformaticsInsights #BioinformaticsInnovation #BioinformaticsAdvancements #BioinformaticsApplications #BioinformaticsChallenges