Methodology for Constructing Problem Definitions in Bioinformatics

Motivation: A recurrent criticism is that certain bioinformatics tools do not account for crucial biology and therefore fail answering the targeted biological question. We posit that the single most important reason for such shortcomings is an inaccurate formulation of the computational problem. Results: Our paper describes how to define a bioinformatics problem so that it captures both the underlying biology and the computational constraints for a particular problem. The proposed model delineates comprehensively the biological problem and conducts an item-by-item bioinformatics transformation resulting in a germane computational problem. This methodology not only facilitates interdisciplinary information flow but also accommodates emerging knowledge and technologies

The Rhodomonas salina mitochondrial genome: bacteria-like operons, compact gene arrangement and complex repeat region

To gain insight into the mitochondrial genome structure and gene content of a putatively ancestral group of eukaryotes, the cryptophytes, we sequenced the complete mitochondrial DNA of Rhodomonas salina. The 48 063 bp circular-mapping molecule codes for 2 rRNAs, 27 tRNAs and 40 proteins including 23 components of oxidative phosphorylation, 15 ribosomal proteins and two subunits of tat translocase. One potential protein (ORF161) is without assigned function. Only two introns occur in the genome; both are present within cox1 belong to group II and contain RT open reading frames. Primitive genome features include bacteria-like rRNAs and tRNAs, ribosomal protein genes organized in large clusters resembling bacterial operons and the presence of the otherwise rare genes such as rps1 and tatA. The highly compact gene organization contrasts with the presence of a 4.7 kb long, repeat-containing intergenic region. Repeat motifs ∼40–700 bp long occur up to 31 times, forming a complex repeat structure. Tandem repeats are the major arrangement but the region also includes a large, ∼3 kb, inverted repeat and several potentially stable ∼40–80 bp long hairpin structures. We provide evidence that the large repeat region is involved in replication and transcription initiation, predict a promoter motif that occurs in three locations and discuss two likely scenarios of how this highly structured repeat region might have evolved

A rotorcraft in-flight ice detection framework using computational aeroacoustics and Bayesian neural networks

This work develops a novel ice detection framework specifically suitable for rotorcraft using computational aeroacoustics and Bayesian neural networks. In an offline phase of the work, the acoustic signature of glaze and rime ice shapes on an oscillating wing are computed. In addition, the aerodynamic performance indicators corresponding to the ice shapes are also monitored. These performance indicators include the lift, drag, and moment coefficients. A Bayesian neural network is subsequently trained using projected Stein variational gradient descent to create a mapping from the acoustic signature generated by the iced wings to predict their performance indicators along with quantified uncertainty that is highly important for time- and safety-critical decision-making scenarios. While the training is carried out fully offline, usage of the Bayesian neural network to make predictions can be conducted rapidly online allowing for an ice detection system that can be used in real time and in-flight

High performance data analysis via coordinated caches

With the second run period of the LHC, high energy physics collaborations will have to face increasing computing infrastructural needs. Opportunistic resources are expected to absorb many computationally expensive tasks, such as Monte Carlo event simulation. This leaves dedicated HEP infrastructure with an increased load of analysis tasks that in turn will need to process an increased volume of data. In addition to storage capacities, a key factor for future computing infrastructure is therefore input bandwidth available per core. Modern data analysis infrastructure relies on one of two paradigms: data is kept on dedicated storage and accessed via network or distributed over all compute nodes and accessed locally. Dedicated storage allows data volume to grow independently of processing capacities, whereas local access allows processing capacities to scale linearly. However, with the growing data volume and processing requirements, HEP will require both of these features. For enabling adequate user analyses in the future, the KIT CMS group is merging both paradigms: popular data is spread over a local disk layer on compute nodes, while any data is available from an arbitrarily sized background storage. This concept is implemented as a pool of distributed caches, which are loosely coordinated by a central service. A Tier 3 prototype cluster is currently being set up for performant user analyses of both local and remote data

Dynamic extensions of batch systems with cloud resources

Compute clusters use Portable Batch Systems (PBS) to distribute workload among individual cluster machines. To extend standard batch systems to Cloud infrastructures, a new service monitors the number of queued jobs and keeps track of the price of available resources. This meta-scheduler dynamically adapts the number of Cloud worker nodes according to the requirement profile. Two different worker node topologies are presented and tested on the Amazon EC2 Cloud service

Genetic Fingerprint of Immunosuppression Following Half-marathon Running in Microarray Study

ABSTRACT Introduction: An acute bout of exhaustive exercise such as marathon or half-marathon running can interfere with immunity, reflected by transient immunosuppression and inflammation like reaction following the event. To gain more insights into these mechanisms, the capacity of whole blood cultures in profiling gene expression in response to endotoxin (LPS) was studied in athletes before, 30min after, 3h after and 24h after a half-marathon run. Methods: Four well trained men and 4 well trained women participated and gene expression patterns were assessed in LPS-stimulated (1h) and unstimulated whole blood using Affymetrix GeneChip microarrays. Results: exercise significantly altered several genes in LPS-stimualted and unstimulated blood cultures of male and female athletes. A row of genes with prominent anti-inflammatory function were strongly up-regulated in unstimulated cultures in both sexes (ARG-1, SOCS3, DUSP-1, BMX, GOS2, CD177, and GJB6). In the same cultures a row of highly inflammatory and apoptotic genes were down-regulated (Granzymes A-M-B-K-H, PRF1, SPON2, Granulysin, KLRF1, PLEKHF1). Some of these genes which were significantly up-or down-regulated in unstimulated cultures were also strongly regulated in LPS-stimulated cultures (GJB6, ARG-1, ORM2, KLRF1, TRA@///TRD@, Granzymes, SPON2). In addition, there were some strongly regulated genes which could only be detected in LPS-stimulated cultures but not in unstimulated cultures. Among these, TNIP3, PLAU, HIVEP1, and SLED were up-regulated and IFN-β, IFN-γ, L-12B, CXCL4. CXCL10 and TRAF1 were significantly down-regulated. Conclusion: there is a row of genes which are strongly regulated through exercise but can only be detected in (endotoxin) stimulated cultures. This is direct evidence showing that the response to pathogens is strongly down-regulated following prolonged exhaustive exercise through different ways

Mobile quantum gravity sensor with unprecedented stability

Changes of surface gravity on Earth are of great interest in geodesy, earth sciences and natural resource exploration. They are indicative of Earth system's mass redistributions and vertical surface motion, and are usually measured with falling corner-cube- and superconducting gravimeters (FCCG and SCG). Here we report on absolute gravity measurements with a mobile quantum gravimeter based on atom interferometry. The measurements were conducted in Germany and Sweden over periods of several days with simultaneous SCG and FCCG comparisons. They show the best-reported performance of mobile atomic gravimeters to date with an accuracy of 39nm/s2, long-term stability of 0.5nm/s2 and short-term noise of 96nm/s2/√Hz. These measurements highlight the unique properties of atomic sensors. The achieved level of performance in a transportable instrument enables new applications in geodesy and related fields, such as continuous absolute gravity monitoring with a single instrument under rough environmental conditions.Peer Reviewe

Parallelized Incomplete Poisson Preconditioner in Cloth Simulation

Efficient cloth simulation is an important problem for interactive applications that involve virtual humans, such as computer games. A common aspect of many methods that have been developed to simulate cloth is a linear system of equations, which is commonly solved using conjugate gradient or multi-grid approaches. In this paper, we introduce to the computer gaming community a recently proposed preconditioner, the incomplete Poisson preconditioner, for conjugate gradient solvers. We show that the parallelized incomplete Poisson preconditioner (PIPP) performs as well as the current state-of-the-art preconditioners, while being much more amenable to standard thread-level parallelism. We demonstrate our results on an 8-core Apple* Mac* Pro and a 32-core code name Emerald Ridge system