Dataset Information

Breaking the computational barriers of pairwise genome comparison.

ABSTRACT: Conventional pairwise sequence comparison software algorithms are being used to process much larger datasets than they were originally designed for. This can result in processing bottlenecks that limit software capabilities or prevent full use of the available hardware resources. Overcoming the barriers that limit the efficient computational analysis of large biological sequence datasets by retrofitting existing algorithms or by creating new applications represents a major challenge for the bioinformatics community.We have developed C libraries for pairwise sequence comparison within diverse architectures, ranging from commodity systems to high performance and cloud computing environments. Exhaustive tests were performed using different datasets of closely- and distantly-related sequences that span from small viral genomes to large mammalian chromosomes. The tests demonstrated that our solution is capable of generating high quality results with a linear-time response and controlled memory consumption, being comparable or faster than the current state-of-the-art methods.We have addressed the problem of pairwise and all-versus-all comparison of large sequences in general, greatly increasing the limits on input data size. The approach described here is based on a modular out-of-core strategy that uses secondary storage to avoid reaching memory limits during the identification of High-scoring Segment Pairs (HSPs) between the sequences under comparison. Software engineering concepts were applied to avoid intermediate result re-calculation, to minimise the performance impact of input/output (I/O) operations and to modularise the process, thus enhancing application flexibility and extendibility. Our computationally-efficient approach allows tasks such as the massive comparison of complete genomes, evolutionary event detection, the identification of conserved synteny blocks and inter-genome distance calculations to be performed more effectively.

SUBMITTER: Torreno O

PROVIDER: S-EPMC4531504 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Breaking the computational barriers of pairwise genome comparison.

Torreno Oscar O Trelles Oswaldo O

BMC bioinformatics 20150811

<h4>Background</h4>Conventional pairwise sequence comparison software algorithms are being used to process much larger datasets than they were originally designed for. This can result in processing bottlenecks that limit software capabilities or prevent full use of the available hardware resources. Overcoming the barriers that limit the efficient computational analysis of large biological sequence datasets by retrofitting existing algorithms or by creating new applications represents a major cha ...[more]

PMID: 26260162

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Project description:Functional recovery after spinal cord injury (SCI) often proves difficult as physical and mental barriers bar survivors from enacting their designated rehabilitation programs. We recently demonstrated that adult mice administered gabapentinoids, clinically approved drugs prescribed to mitigate chronic neuropathic pain, recovered upper extremity function following cervical SCI. Given that rehabilitative training enhances neuronal plasticity and promotes motor recovery, we hypothesized that the combination of an aerobic-based rehabilitation regimen like treadmill training with gabapentin (GBP) administration will maximize recovery in SCI mice by strengthening synaptic connections along the sensorimotor axis. Whereas mice administered GBP recovered forelimb functions over the course of weeks and months following SCI, no additive forelimb recovery as the result of voluntary treadmill training was noted in these mice. To our surprise, we also failed to find an additive effect in mice administered vehicle. As motivation is crucial in rehabilitation interventions, we scored active engagement toward the rehabilitation protocol and found that mice administered GBP were consistently participating in the rehabilitation program. In contrast, mice administered vehicle exhibited a steep decline in participation, especially at chronic time points. Whereas neuroinflammatory gene expression profiles were comparable between experimental conditions, we discovered that mice administered GBP had increased hippocampal neurogenesis and exhibited less anxiety-like behavior after SCI. We also found that an external, social motivator effectively rescues participation in mice administered vehicle and promotes forelimb recovery after chronic SCI. Thus, not only does a clinically relevant treatment strategy preclude the deterioration of mental health after chronic SCI, but group intervention strategies may prove to be physically and emotionally beneficial for SCI individuals.

Dataset Information

Breaking the computational barriers of pairwise genome comparison.

Publications

Breaking the computational barriers of pairwise genome comparison.

Similar Datasets

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