21,525 research outputs found
MOLNs: A cloud platform for interactive, reproducible and scalable spatial stochastic computational experiments in systems biology using PyURDME
Computational experiments using spatial stochastic simulations have led to
important new biological insights, but they require specialized tools, a
complex software stack, as well as large and scalable compute and data analysis
resources due to the large computational cost associated with Monte Carlo
computational workflows. The complexity of setting up and managing a
large-scale distributed computation environment to support productive and
reproducible modeling can be prohibitive for practitioners in systems biology.
This results in a barrier to the adoption of spatial stochastic simulation
tools, effectively limiting the type of biological questions addressed by
quantitative modeling. In this paper, we present PyURDME, a new, user-friendly
spatial modeling and simulation package, and MOLNs, a cloud computing appliance
for distributed simulation of stochastic reaction-diffusion models. MOLNs is
based on IPython and provides an interactive programming platform for
development of sharable and reproducible distributed parallel computational
experiments
Virtual Environment for Next Generation Sequencing Analysis
Next Generation Sequencing technology, on the one hand, allows a more accurate analysis, and, on the other hand, increases the amount of data to process. A new protocol for sequencing the messenger RNA in a cell, known as RNA- Seq, generates millions of short sequence fragments in a single run. These fragments, or reads, can be used to measure levels of gene expression and to identify novel splice variants of genes. The proposed solution is a distributed architecture consisting of a Grid Environment and a Virtual Grid Environment, in order to reduce processing time by making the system scalable and flexibl
Applications and Challenges of Real-time Mobile DNA Analysis
The DNA sequencing is the process of identifying the exact order of
nucleotides within a given DNA molecule. The new portable and relatively
inexpensive DNA sequencers, such as Oxford Nanopore MinION, have the potential
to move DNA sequencing outside of laboratory, leading to faster and more
accessible DNA-based diagnostics. However, portable DNA sequencing and analysis
are challenging for mobile systems, owing to high data throughputs and
computationally intensive processing performed in environments with unreliable
connectivity and power.
In this paper, we provide an analysis of the challenges that mobile systems
and mobile computing must address to maximize the potential of portable DNA
sequencing, and in situ DNA analysis. We explain the DNA sequencing process and
highlight the main differences between traditional and portable DNA sequencing
in the context of the actual and envisioned applications. We look at the
identified challenges from the perspective of both algorithms and systems
design, showing the need for careful co-design
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