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With a goal of providing a one-stop platform, this framework brings our following repositories for digital biology under one umbrella:
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* Architecture efficient versions of several popular applications as part of our toolkit layer
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| Original Application | Our architecure-efficient version |
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| --- | --- |
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| Short read sequence mapping tool, [BWA-MEM](https://github.com/lh3/bwa)|[BWA-MEM2](https://github.com/bwa-mem2/bwa-mem2)|
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| long read sequence mapping tool, [minimap2](https://github.com/lh3/minimap2)|[mm2-fast](https://github.com/bwa-mem2/mm2-fast)|
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| Deep learning based variant calling tool, [DeepVariant](https://github.com/google/deepvariant)|[Open-Omics-DeepVariant](https://github.com/IntelLabs/open-omics-deepvariant)|
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| Deep learning based tool for protein structure prediction, [AlphaFold2](https://github.com/google-deepmind/alphafold)|[Open-Omics-AlphaFold](https://github.com/IntelLabs/open-omics-alphafold)|
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| Tool for biological sequence analysis using profile HMMs, [HMMER](https://github.com/EddyRivasLab/hmmer)|[IntelLabs HMMER](https://github.com/IntelLabs/hmmer)|
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| Tool for HMM based sensitive protein sequence searching, [HH-suite](https://github.com/soedinglab/hh-suite)|[IntelLabs HH-suite](https://github.com/IntelLabs/hh-suite)|
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*[Trans-Omics Acceleration Library](https://github.com/IntelLabs/Trans-Omics-Acceleration-Library): As part of our building blocks layer, this is a library containing architecture-efficient versions of key algorithms and data structures used for Omics analysis.
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In addition, we also use several existing AI libraries: oneDNN, oneDAL, oneCCL, Katana Graph, LIBXSMM.
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# Getting Started
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```sh
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# Download release
@@ -34,7 +50,7 @@ cd pipelines
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# Go to the directory with toolkit
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cd applications
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# Go to the directory with biology building blocks
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# Go to the directory with biology building blocks to access Trans-Omics Acceleration Library
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