One of the solutions proposed for addressing the challenge of the overwhelming abundance of genomic sequence and other biological data is the use of the Hadoop computing framework. Appropriate tools are needed to set ...
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One of the solutions proposed for addressing the challenge of the overwhelming abundance of genomic sequence and other biological data is the use of the Hadoop computing framework. Appropriate tools are needed to set up computational environments that facilitate research of novel bioinformatics methodology using Hadoop. Here, we present cl-dash, a complete starter kit for setting up such an environment. Configuring and deploying new Hadoop clusters can be done in minutes. Use of Amazon Web Services ensures no initial investment and minimal operation costs. Two sample bioinformatics applications help the researcher understand and learn the principles of implementing an algorithm using the MapReduce programming pattern.
Advances in sequencing capacity have led to the generation of unprecedented amounts of genomic data. The processing of this data frequently leads to I/O bottlenecks, e.g. when analyzing a small genomic region across a...
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Advances in sequencing capacity have led to the generation of unprecedented amounts of genomic data. The processing of this data frequently leads to I/O bottlenecks, e.g. when analyzing a small genomic region across a large number of samples. The largest I/O burden is, however, often not imposed by the amount of data needed for the analysis but rather by index files that help retrieving this data. We have developed chopBAI, a program that can chop a BAM index (BAI) file into small pieces. The program outputs a list of BAI files each indexing a specified genomic interval. The output files are much smaller in size but maintain compatibility with existing software tools. We show how preprocessing BAI files with chopBAI can lead to a reduction of I/O by more than 95% during the analysis of 10 kb genomic regions, eventually enabling the joint analysis of more than 10 000 individuals. Availability and Implementation: The software is implemented in C++, GPL licensed and available at http://***/DecodeGenetics/chopBAI
The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow t...
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The most important features of error correction tools for sequencing data are accuracy, memory efficiency and fast runtime. The previous version of BLESS was highly memory-efficient and accurate, but it was too slow to handle reads from large genomes. We have developed a new version of BLESS to improve runtime and accuracy while maintaining a small memory usage. The new version, called BLESS 2, has an error correction algorithm that is more accurate than BLESS, and the algorithm has been parallelized using hybrid MPI and OpenMP programming. BLESS 2 was compared with five top-performing tools, and it was found to be the fastest when it was executed on two computing nodes using MPI, with each node containing twelve cores. Also, BLESS 2 showed at least 11% higher gain while retaining thememory efficiency of the previous version for large genomes. Availability and implementation: Freely available at https://***/projects/bless-ecContact:dchen@***
The article provides an overview of the gas turbine disc failure and explores the disc life laws and procedure. The Life-To-First-Crack (LTFC) approach is based on the premise which a safe service disc life can be got...
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The article provides an overview of the gas turbine disc failure and explores the disc life laws and procedure. The Life-To-First-Crack (LTFC) approach is based on the premise which a safe service disc life can be gotten through testing a sample of engine discs in a spin pit. The Retirement For Cause (RFC) permits an aircraft engine disc to be applied for the full extent of its safe fatigue life, bypassing the LTFC algorithm's conservatism.
Application of computational methods in drug discovery has received increased attention in recent years as a way to accelerate drug target prediction. Based on 443 sequence-derived protein features, we applied the mos...
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Application of computational methods in drug discovery has received increased attention in recent years as a way to accelerate drug target prediction. Based on 443 sequence-derived protein features, we applied the most commonly used machine learning methods to predict whether a protein is druggable as well as to opt for superior algorithm in this task. In addition, feature selection procedures were used to provide the best performance of each classifier according to the optimum number of features. When run on all features, Neural Network was the best classifier, with 89.98% accuracy, based on a k-fold cross-validation test. Among all the algorithms applied, the optimum number of most-relevant features was 130, according to the Support Vector Machine-Feature Selection (SVM-FS) algorithm. This study resulted in the discovery of new drug target which potentially can be employed in cell signaling pathways, gene expression, and signal transduction. The DrugMiner web tool was developed based on the findings of this study to provide researchers with the ability to predict druggable proteins. DrugMiner is freely available at ***.
In this work we propose an extension of logic programming, under the stable model semantics, and the action language BC where rule bodies and causal laws may contain a new kind of literal, that we call causal literal,...
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In this work we propose an extension of logic programming, under the stable model semantics, and the action language BC where rule bodies and causal laws may contain a new kind of literal, that we call causal literal, that allows us to inspect the causal justifications of standard atoms. To this aim, we extend a recently proposed semantics where each atom belonging to a stable model is associated with a justification in the form of an algebraic expression (which corresponds to a logical proof built with rule labels). In particular, we use causal literals for evaluating and deriving new conclusions from statements like "A has been sufficient to cause B." We also use the proposed semantics to extend the action language BC with causal literals and, by some examples, show how this action language is useful for expressing a high level representation of some typical Knowledge Representation examples involving causal knowledge.
Acyclicity constraints are prevalent in knowledge representation and applications where acyclic data structures such as DAGs and trees play a role. Recently, such constraints have been considered in the satisfiability...
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Acyclicity constraints are prevalent in knowledge representation and applications where acyclic data structures such as DAGs and trees play a role. Recently, such constraints have been considered in the satisfiability modulo theories (SMT) framework, and in this paper we carry out an analogous extension to the answer set programming (ASP) paradigm. The resulting formalism, ASP modulo acyclicity, offers a rich set of primitives to express constraints related to recursive structures. In the technical results of the paper, we relate the new generalization with standard ASP by showing (i) how acyclicity extensions translate into normal rules, (ii) how weight constraint programs can be instrumented by acyclicity extensions to capture stability in analogy to unfounded set checking, and (iii) how the gap between supported and stable models is effectively closed in the presence of such an extension. Moreover, we present an efficient implementation of acyclicity constraints by incorporating a respective propagator into the state-of-the-art ASP solver CLASP. The implementation provides a unique combination of traditional unfounded set checking with acyclicity propagation. In the experimental part, we evaluate the interplay of these orthogonal checks by equipping logic programs with supplementary acyclicity constraints. The performance results show that native support for acyclicity constraints is a worthwhile addition, furnishing a complementary modeling construct in ASP itself as well as effective means for translation-based ASP solving.
The author comments on a study which explored an energy-efficient implementation of an artificial neural network. Particular focus is given to the use of learning algorithm in an artificial neural network, as well as ...
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The author comments on a study which explored an energy-efficient implementation of an artificial neural network. Particular focus is given to the use of learning algorithm in an artificial neural network, as well as neuron models used in energy-efficient hardware. Also mentioned are implementation of convolutional neural networks on the TrueNorth chip, questions raised by the study and the backprop algorithm.
The article presents a study published by musician Rie Takahashi and genetics professor Jeffrey H. Miller on the integration of DNA sequences to music. Topics discussed include the development of the Gene2Music comput...
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The article presents a study published by musician Rie Takahashi and genetics professor Jeffrey H. Miller on the integration of DNA sequences to music. Topics discussed include the development of the Gene2Music computer algorithm which turns protein sequences into musical notes, the assignment of notes into the nucleotides of a DNA sequence, and the use of Gene2Music in the representation of the huntingtin protein mutation which causes the Huntington's disease.
The anaesthesia team has been defined by the Association of Anaesthetists of Great Britain and Ireland and mandates the need for a trained anaesthetic assistant,1 who may be either a nurse or an operating department p...
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The anaesthesia team has been defined by the Association of Anaesthetists of Great Britain and Ireland and mandates the need for a trained anaesthetic assistant,1 who may be either a nurse or an operating department practitioner (ODP). It has also been acknowledged that teamwork is crucial to obtain the best results in a crisis.2-6 I would like to present a protocol originally developed for ODPs7 that dovetails with the Difficult Airway Guidelines, named Co-PILOT (Co, Confirm failure; P, Propose other equipment; I, Immediate senior anaesthetic assistance to be called; L, Laryngeal mask airway (second generation); O, Oxygenate; and T, Tracheal access; Fig.?1). It has since been expanded to the role of the anaesthetic assistant during unanticipated difficulty whatever their training, nursing or ODP, with the aim to improve teamwork.8
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