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In the most productive biotech companies, both bench scientists and computational biologists contribute to analysis. So why are they using tools that are incompatible? Bench scientists need flexible and intuitive tools. But that flexibility often leads to data being stored in inconsistent, non-machine readable formats. To make matters even more difficult, it’s usually stored on laptops or file shares in vaguely named file paths. Meanwhile, comp bio teams use code-based tools that require deep technical experience and store the data in the cloud — rendering it inaccessible to bench scientists. For these two groups to work together, they need tools that are both intuitive for bench scientists and compatible with computational tools. That’s why we’re building Sphinx Bio: a platform for scientists to quickly and easily perform analysis while still providing the consistent, compute-friendly data that digital teams expect.

Basepair + AWS HealthOmics: A Game-Changing Height Advantage in Genomic Analysis It’s the end of Olympics!!! We couldn’t help but recall this image of a 2019 junior basketball game between the USA and El Salvador. One team towers over the other, with a clear height advantage that's impossible to ignore. And it got us thinking that's exactly how Basepair and AWS HealthOmics stack up against traditional genomic analysis approaches. Just like the taller team has a natural edge on the court, our combined solution offers unparalleled advantages: 1. Reach: Process vast amounts of genomic data faster than ever before. 2. Agility: Quickly adapt to new research requirements with flexible cloud infrastructure. 3. Precision: Leverage advanced machine learning tools like Alphafold for more accurate insights. 4. Efficiency: Use GPU- accelerated versions of tools like Nvidia Parabricks Deep Variant to reduce costs and time-to-results significantly. Don't let your genomic research get outplayed. Level up with Basepair and AWS HealthOmics and stand tall in the world of bioinformatics! #GenomicAnalysis #CloudComputing #Bioinformatics #AWSHealthOmics #Basepair #aws #healthomics #research #development #NvidiaParabricks #nvidia #olympics

Cost-effective genomics analysis with Sentieon on Azure. This Blog was Co-Authored by Don Freed - Sr. Bioinformatics Scientist, Brendan Gallagher - Head of Business Development at Sentieon, Inc.  Introduction   In our previous blog, we introduced you to Sentieon, who specializes in developing software tools for analyzing genomic data. Sentieon pipelines allow researchers and clinicians to process and analyze genomic data quickly, accurately, and efficiently with a low total cost of ownership. To understand the performance of the Sentieon software, we benchmarked Sentieon’s DNAseq and DNAscope pipelines version 202112.05, using... #techcommunity #azure #microsoft https://lnkd.in/gTbAZjEA

Forget clouds, it seems the new place to save our files are DNA strands! Tech's storage journey: floppy disks, CDs, cloud... and now, DNA? Yup, you read that right! French startup Biomemory is turning your body's building blocks into storage units. Here's the scoop: 1. Input text on Biomemory’s site converted from zeros and ones to DNA code (A’s, C’s, G’s, T’s). 2. Biomemory crafts a custom DNA strand, seals it in a silver card. 3. $1k gets you 2 cards, each holding a kilobyte of data for ~150 years – well gone are the days of short-lived hard drives! 4. Ready to access? Mail in your card, get it rehydrated, read by a sequencing machine, and voila! Why is this wild? Well: - 1 gram of DNA = 36 million copies of Avengers: Endgame. - As data creation skyrockets, DNA could be our storage superhero. - DNA storage = zero energy until retrieval, unlike power-hungry data centers. Microsoft and Twist Bioscience are in on the DNA party, too. They've stored entire songs – because why not? But like with every bio medical invention, this one is prone to doubts too! While this is a concept that is not entirely new, the real use cases have started to pop now and hence the implementation at large scale can happen sooner rather than later. #techevolution

📊 How to make the most of your data: Clear and effective visualizations are essential for gaining insights and making informed decisions. With Code Ocean’s Compute Capsule, you can easily turn complex biological data into visual outputs using your favorite libraries. Here’s what Code Ocean can do for you: 🔍 Explore Data: Dive deep with integrated Cloud Workstations, from Notebook-type analyses in JupyterLab, to no-code applications in Shiny. 🤝 Collaborate Effortlessly: Share and iterate in real-time with your team. Entire analyses can be easily shared with 1-click. 📈 Create Trusted Science: Results generated come with automated lineage and provenance. Results are traceable and reproducible over any time horizon. Whether you’re creating heat maps for gene expression profiling, browsing genomic annotation in IGV, or analyzing protein-protein interactions with network diagrams, Code Ocean is your go-to platform for making data visualization a breeze. Check out an example below! Learn more about Code Ocean's Compute Capsules: https://lnkd.in/e6Ba9iwC #Biotechnology #Bioinformatics #DataAnalytics #LLMs #GenAI #ComputationalBiology #Genomics #ComputationalScience

Thrilled to announce our collaboration with Dovetail Bio Partners, revolutionizing bioinformatics. Together, we redefine genomics workflows for enhanced repeatability and scalability. dovetail biopartners Daniel Dacey 🐦 Our journey starts with preprocessing, transitioning exome sequences from SRA to FASTQ format. Variant calling, powered by the Nextflow-based Sarek pipeline, identifies SNP mutations, generating detailed VCF files. Moving forward, we filter VCF files to spotlight genes of interest, creating a robust data-frame for analytics. The solution seamlessly integrates with AWS Batch, offering scalability and dynamic cost optimization. Resources scale based on demand, ensuring cost-effectiveness without compromising performance. A key aspect to our solution is Amazon SageMaker. With an intuitive IDE, it simplifies analytics and accelerates insights. Managed notebooks streamline collaboration, reducing development time. SageMaker's pay-as-you-go aligns with cost-effectiveness. Pay only for resources used during development, training, and deployment, complemented by AWS Batch's dynamic scaling. We're exploring edge-node networks or SageMaker's ML for custom graph neural networks. We're excited to introduce a standardized, efficient, and cost-optimized genomics workflow. Stay tuned for more insights as we shape the future of bioinformatics! #Bioinformatics #GenomicsResearch #AWSBatch #SageMaker #Collaboration

Hello Connections! I am glad to share the future of data storage. 🧬Unlocking the Future of Data Storage: Harnessing DNA's Potential In the fast-evolving world of technology⚙️, innovation is key🔑 to meet the growing demands for data storage. But the Traditional methods, such as hard drives💿 and cloud storage☁️, have served us well, but they are reaching their limits now. So we have new way of storing data that is "#DNAstorage". DNA, the molecule that carries the genetic instructions for all living organisms, which is nature's own information storage system. How does #DNAstorage work.?🤔 Instead of encoding data in binary digits (0s and 1s) like traditional storage methods, DNA stores information using the four nucleotide bases: adenine (A), cytosine (C), guanine (G), and thymine (T). Using advanced techniques, such as DNA 🧬synthesis and sequencing, data can be encoded into DNA 🧬strands and decoded back into its original form when needed and with its incredible density and stability, DNA 🧬can store vast amounts of data in a tiny space for thousands of years. "It is estimated that 1 gram of DNA🧬 can hold up to 215 #petabytes of information". This has the potential to significantly reduce the carbon footprint associated with data centers. Currently, the process of encoding and decoding data into DNA🧬is slow and expensive, primarily due to the complexity of DNA🧬 synthesis and sequencing technologies. However in future research and advancements in #biotechnology are steadily driving down costs and improving efficiency, with harnessing the power of nature's own code, we can unlock a future where data is stored securely and sustainably for generations to come. Currently #Microsoft and #UNIVERSITYOFWASHINGTON are researching on this DNA storage #technology.🧬 #DNATechonology #Innovation #NewTechnology #Future #Data #Technology

https://lnkd.in/gXcEFt8c Legacy technologies traditionally relied on CPU- or FPGA-based architectures for data analysis, but Ultima Genomics takes advantage of advances in GPU computing, machine learning (ML), and cloud technology to boost its analytics capabilities. Using solutions from Amazon Web Services (AWS), Ultima can spin up development environments quickly and innovate faster. Ultima also uses Amazon Web Services (AWS) to train the ML algorithms that it uses for basecalling—translating raw signals into nucleotide sequences—a crucial technical task in genomics. “Using AWS, we can take challenging computational tasks and deliver a solution for them,” says Omer Barad, vice president of genomic solutions at Ultima. “We can scale to immediately start seeing benefits and use ML to generate accurate results from our billions of data points.” #aws #ultima #genomics

https://lnkd.in/gD4FgKa5 Easy-to-run protein algorithms for a range of open-source molecular models, demostrating how AWS can significantly reduce the cost and time needed to generate usable protein structures. Access Ready2Run workflows within the Amazon HealthOmics services for single API or console deployment of AlphaFold and ESMFold algorithms with transparent , run-based pricing and scalable infrastructure. #aws #protein

Some weeks ago I wrote an article on how Med#Gemini was handling clinical data and able to summarize clinical report from images ⚕️😷🏥:  https://lnkd.in/duTJFHEk However, Google Gemini and his brother MedGemini are nothing but opensource Now we have the opensource and open-database version 📖📖📖: "NExT-GPT: Any-to-Any #Multimodal LLM" Preprint article: https://lnkd.in/dxy9zE7i Project page: https://lnkd.in/dTdZRg_P #LLM #datascience #GenerativeAI