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.NET for Apache Spark provides high-performance APIs for using Apache Spark from C# and F#. With these .NET APIs, you can access the most popular Dataframe and SparkSQL aspects of Apache Spark, for working with structured data, and Spark Structured Streaming, for working with streaming data. .NET for Apache Spark is compliant with .NET Standard - a formal specification of .NET APIs that are common across .NET implementations. This means you can use .NET for Apache Spark anywhere you write...

DocWire SDK, a standout C++20AI driven data processing tool, has received award from SourceForge and strong backing from Microsoft. It handles nearly 100 file types, empowering efficient text extraction, web data extraction, and document analysis. For businesses, the shift to DocWire SDK signifies a leap forward. It promises comprehensive document format support and the ability to extract valuable insights from email boxes, databases, and websites using cutting-edge AI. DocWire SDK aims to...

123VCF has been developed to make the filtration step of VCF files efficient and more importantly easy to understand. It can be used in the most important step of whole exome/genome sequencing data analysis in the research and also clinical settings. User manual: https://dl.adbioinformatics.net/123VCF/123VCF_Manual.ver2.pdf If you use 123VCF, please cite its paper: Eidi, M., Abdolalizadeh, S., Moeini, S. et al. 123VCF: an intuitive and efficient tool for filtering VCF files. BMC...

log4jscanner is a filesystem scanner and Go package that helps organizations quickly identify vulnerable Log4j components inside JARs and shaded dependencies. Instead of probing networks, it walks directories and archives, including nested JARs, to find version fingerprints and risky classes associated with the Log4Shell family of issues. The focus on static analysis makes it suitable for container images, build artifacts, and offline systems where active scanning isn’t feasible. Clear,...

...QuickRNASeq takes advantage of parallel computing resources, a careful selection of previously published algorithms for RNA-seq read mapping, counting and quality control, and a three-stage strategy to build a fully automated workflow. We also implemented built-in functionalities to detect sample swapping or mislabeling in large-scale RNA-seq studies. Our pipeline significantly lifts large-scale RNA-seq data analysis to the next level of automation and visualization. Please take a look at our test run project report and get a taste of its rich interactive visualization features. http://baohongz.github.io/QuickRNASeq QuickRNASeq user guide can be downloaded or is accessible online as well http://baohongz.github.io/QuickRNASeq/guide.html For more on QuickRNASeq, please see our paper http://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-015-2356-9 Enjoy QuickRNASeq

Census is a comprehensive cross-platform project manager and integration hub for NONMEM, the gold standard tool for model-based pharmacometric data analysis.