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WDL 1.2.0: Enhancing Workflow Description Language for Bioinformatics
The Workflow Description Language (WDL) team has announced the release of WDL 1.2.0, a significant update to improve workflow descriptions' flexibility and usability in bioinformatics. This new version introduces several key features and enhancements that promise to streamline workflow management and execution, making it easier for developers and researchers to implement and manage workflows.
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MIT Researchers Use Explainable AI Model to Discover New Antibiotics
Researchers from MIT's Collins lab used an explainable deep-learning model to discover chemical compounds which could fight the MRSA bacteria. The model uses graph algorithms to identify chemical compounds which are likely to have antibiotic properties. Additional models predict whether or not the chemicals would be harmful to humans.
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Pfizer Uses Serverless Architecture on AWS to Scale Processing of Digital Biomarkers
Pfizer upgraded the serverless architecture for processing digital biomarker data at scale to make it more flexible and configurable. They created a framework that uses a file processing pipeline built with AWS Step Functions and other serverless services, as well as a custom Python package for data ingestion and processing.
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Meta's Genomics AI ESMFold Predicts Protein Structure 6x Faster Than AlphaFold2
Meta AI Research recently announced ESMFold, an AI model for predicting protein structure from a sequence of genes. ESMFold is built on a 15B parameter Transform model and achieves accuracy comparable to other state-of-the-art models with an order-of-magnitude inference time speedup.
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DeepMind's AlphaFold2 AI Solves 50-Year-Old Biology Challenge
The Protein Structure Prediction Center announced that AlphaFold2, an AI system developed by DeepMind, has solved its Protein Structure Prediction challenge. AlphaFold2 achieved a median score of 92.4 on the Global Distance Test (GDT) metric, above the threshold considered competitive with traditional methods.
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ML-Assisted Biochip Used for Real-Time Single Cancer Cell Analysis
Researchers and engineers at UCI recently created a machine learning-assisted biochip that can both examine and differentiate between cancers and healthy tissues at the single cell level. The data produced by the device can be used to study tumor heterogeneity, which can help reduce resistance to cancer therapies.
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Microsoft Makes Cloud-Based Biological Research Tool Open Source
Bio Model Analyzer, a Microsoft cloud-based tool that biologists can use to model cell interactions and communications, is now available as open-source on GitHub. It is used to create computer models that can compare the processes within healthy and diseased cells. Scientists can see the interactions between millions of genes and proteins, speeding up research and treatment of diseases.
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Cloudera Announces Partnership with the Broad Institute
Cloudera announced their partnership with MIT & Harvard's Broad Institute and detailed some of their experience with the Genome Analytics Toolkit pipeline.
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Precision Medicine Modeling Demonstration with Spark on EMR, ADAM, and the 1000 Genomes Project
AWS engineers Christopher Crosbie and Ujjwal Ratan detail using Spark on EMR for precision medicine data analysis on the ADAM platform with data from the 1000 genomes project.
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The Broad Institute Migrates Genome Sequencing Pipeline to Google Cloud Platform
Genomic data sequencing and subsequent analysis faces large data volume challenges that several organizations are solving with cloud services. The Broad Institute detailed their experience with petabyte scale sequencing pipelines last month through the Google Research Blog and is detailed here by InfoQ.
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NCBI BLAST for Windows Azure
Microsoft is now offering NCBI BLAST for the Windows Azure platform. NCBI BLAST was created by a group of researchers working for the National Institutes of Health, a division of the United States Department of Health and Human Services. NCBI describes BLAST as a tool that “finds regions of local similarity between sequences” of protein and DNA chains.
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Microsoft Enters the Biotech Market with a Truly Open Source Project
Microsoft Biology Foundation is a collection of libraries build on the .NET framework and based on traditional open source traditions. Rather than reinvent the wheel, Microsoft is leveraging the file formats already found in bioinformatics community. Even more unusual for them, they are soliciting contributions to be added to future versions of MBF.