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This is a pertinent need since most analytical tools for structural analysis require large computational infrastructure.
AnMol is meant to fill this need and provide a platform for tools that end users can install locally and use without investing in large computational infrastructure.
As pointed out in Knebe et al. (2013) there is a general trend towards 'on-the-fly' analysis for many reasons: most modern astrophysical simulations are performed on large computational infrastructure with distributed memory.
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Motivation: The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures.
The software can be used by both large-scale bioinformatics projects and administrators of large computational infrastructures that provide services based on well-known bioinformatics suites such as EMBOSS, Sequence Retrieval System (SRS) (Etzold et al., 1996), (http://www.biowisdom.com/navigation/srs/srs) and GCG.
However, besides the large amount of computational infrastructure required, the key challenge to this approach is the partitioning of reads into components representing transcript isoforms.
Deep learning models are inherently computationally complex and require many-core CPUs and large-scale computational infrastructures.
Due to the practical impossibility of moving all the data across geographical dispersed sites, there is the need of computational infrastructure able to combine large storage facilities and HPC.
Outside of clinical science, many organizations are exploring or using cloud computing technology to fulfill computational infrastructure needs.
But, as someone whose work focuses on computational biology, and at the intersection of biology and big data, I am confident that computational infrastructure is the vital ingredient to help the recommendations become reality.
Until large-scale reference data became available, the attributes of the computational infrastructure were postulated by many, but have mostly remained unverified.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com