An integrative approach to inferring biologically meaningful gene modules

<p>Abstract</p> <p>Background</p> <p>The ability to construct biologically meaningful gene networks and modules is critical for contemporary systems biology. Though recent studies have demonstrated the power of using gene modules to shed light on the functioning of complex biological systems, most modules in these networks have shown little association with meaningful biological function. We have devised a method which directly incorporates gene ontology (GO) annotation in construction of gene modules in order to gain better functional association.</p> <p>Results</p> <p>We have devised a method, Semantic Similarity-Integrated approach for Modularization (SSIM) that integrates various gene-gene pairwise similarity values, including information obtained from gene expression, protein-protein interactions and GO annotations, in the construction of modules using affinity propagation clustering. We demonstrated the performance of the proposed method using data from two complex biological responses: 1. the osmotic shock response in <it>Saccharomyces cerevisiae</it>, and 2. the prion-induced pathogenic mouse model. In comparison with two previously reported algorithms, modules identified by SSIM showed significantly stronger association with biological functions.</p> <p>Conclusions</p> <p>The incorporation of semantic similarity based on GO annotation with gene expression and protein-protein interaction data can greatly enhance the functional relevance of inferred gene modules. In addition, the SSIM approach can also reveal the hierarchical structure of gene modules to gain a broader functional view of the biological system. Hence, the proposed method can facilitate comprehensive and in-depth analysis of high throughput experimental data at the gene network level.</p

ANTERIOR CRUCIATE LIGAMENT INJURY RISK FACTORS DIFFERENCES BETWEEN FEMALE DANCERS AND FEMALE SOCCER PLAYERS DURING SINGLE-LEGGED AND DOUBLE LEGGED LANDING TASKS

The purpose of this study was to compare ACL injury risk factors between female dancers and female soccer players during single-legged drop landing and double legged drop landing vertical jump tasks. Fifteen elite female soccer players and 45 professional female dancers (15 ballet, 15 modern, and 15 Korean dancers) were recruited to participate in this study. Two-way repeated measure of ANOVAs (participant groups & landing tasks, 4x2) were used. Female dancers landed with a significantly lower trunk flexion, trunk external rotation, knee external rotation, and knee valgus moment than those of female soccer players. Also, single-legged drop landing task demonstrated a higher trunk external rotation and knee valgus moment than those of double legged drop landing vertical jump task

New gene selection method for classification of cancer subtypes considering within-class variation

AbstractIn this work we propose a new method for finding gene subsets of microarray data that effectively discriminates subtypes of disease. We developed a new criterion for measuring the relevance of individual genes by using mean and standard deviation of distances from each sample to the class centroid in order to treat the well-known problem of gene selection, large within-class variation. Also this approach has the advantage that it is applicable not only to binary classification but also to multiple classification problems. We demonstrated the performance of the method by applying it to the publicly available microarray datasets, leukemia (two classes) and small round blue cell tumors (four classes). The proposed method provides a very small number of genes compared with the previous methods without loss of discriminating power and thus it can effectively facilitate further biological and clinical researches

Turbo Warrants under Hybrid Stochastic and Local Volatility

This paper considers the pricing of turbo warrants under a hybrid stochastic and local volatility model. The model consists of the constant elasticity of variance model incorporated by a fast fluctuating Ornstein-Uhlenbeck process for stochastic volatility. The sensitive structure of the turbo warrant price is revealed by asymptotic analysis and numerical computation based on the observation that the elasticity of variance controls leverage effects and plays an important role in characterizing various phases of volatile markets

Adaptive Navigation Control for Swarms of Autonomous Mobile Robots

This paper was devoted to developing a new and general coordinated adaptive navigation scheme for large-scale mobile robot swarms adapting to geographically constrained environments. Our distributed solution approach was built on the following assumptions: anonymity, disagreement on common coordinate systems, no pre-selected leader, and no direct communication. The proposed adaptive navigation was largely composed of four functions, commonly relying on dynamic neighbor selection and local interaction. When each robot found itself what situation it was in, individual appropriate ranges for neighbor selection were defined within its limited sensing boundary and the robots properly selected their neighbors in the limited range. Through local interactions with the neighbors, each robot could maintain a uniform distance to its neighbors, and adapt their direction of heading and geometric shape. More specifically, under the proposed adaptive navigation, a group of robots could be trapped in a dead-end passage,but they merge with an adjacent group to emergently escape from the dead-end passage. Furthermore, we verified the effectiveness of the proposed strategy using our in-housesimulator. The simulation results clearly demonstrated that the proposed algorithm is a simple yet robust approach to autonomous navigation of robot swarms in highlyclutteredenvironments. Since our algorithm is local and completely scalable to any size, it is easily implementable on a wide variety of resource-constrained mobile robots andplatforms. Our adaptive navigation control for mobile robot swarms is expected to be used in many applications ranging from examination and assessment of hazardous environments to domestic applications

Effects of Body Mass Index on Ankle Joint Muscle Function and Dynamic Proprioceptive Control

PURPOSE Increased body mass index (BMI) increases ankle instability and adversely affects human movement. This study aims to compare and analyze the muscle function and proprioception of the ankle joint based on Body Mass Index (BMI) to determine potential differences. METHODS Twenty-eight healthy male and female college students were categorized into overweight (≥ BMI 23) and normal (< BMI 23) groups. Measurements included BMI, isokinetic strength of dorsiflexion, plantarflexion, eversion, inversion, ankle joint range of motion, and ankle joint proprioception. RESULTS In dorsiflexion, right 30°/sec (p=.035), left 30°/sec (p=.009) and right 120°/sec (p=.011); in plantarflexion, left 30°/sec (p<.001), right 120°/sec (p=.007) and left 120°/sec (p=.006) in ankle inversion, left 30°/sec (p=.001), right 120°/sec (p=.021) and left 120°/sec (p=.007), left 30°/sec (p=.014), 120°/sec (p=.001) in ankle inversion-eversion ratio, right (p=.003) and left (p=.003) in ankle joint range of motion, right (p<.001) and left (p=.022) in total proprioception, and left (p<.001) in left-right proprioception were significantly different between the normal and overweight groups. CONCLUSIONS It was found that the overweight group had lower muscle strength, joint range of motion, and proprioceptive control function of the ankle joint than the normal group according to BMI. Therefore, exercise programs should be provided to strengthen the periarticular muscles involved in ankle movement, such as the tibialis anterior, soleus, and peroneus longus, and to control dynamic proprioception to prevent ankle injuries and function of the ankle joint according to BMI