Implementation of network entropy algorithms on hpc machines, with application to high-dimensional experimental data

Network Theory is a prolific and lively field, especially when it approaches Biology. New concepts from this theory find application in areas where extensive datasets are already available for analysis, without the need to invest money to collect them. The only tools that are necessary to accomplish an analysis are easily accessible: a computing machine and a good algorithm. As these two tools progress, thanks to technology advancement and human efforts, wider and wider datasets can be analysed. The aim of this paper is twofold. Firstly, to provide an overview of one of these concepts, which originates at the meeting point between Network Theory and Statistical Mechanics: the entropy of a network ensemble. This quantity has been described from different angles in the literature. Our approach tries to be a synthesis of the different points of view. The second part of the work is devoted to presenting a parallel algorithm that can evaluate this quantity over an extensive dataset. Eventually, the algorithm will also be used to analyse high-throughput data coming from biology.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Using incomplete citation data for MEDLINE results ranking.

Information overload is a significant problem for modern medicine. Searching MEDLINE for common topics often retrieves more relevant documents than users can review. Therefore, we must identify documents that are not only relevant, but also important. Our system ranks articles using citation counts and the PageRank algorithm, incorporating data from the Science Citation Index. However, citation data is usually incomplete. Therefore, we explore the relationship between the quantity of citation information available to the system and the quality of the result ranking. Specifically, we test the ability of citation count and PageRank to identify "important articles" as defined by experts from large result sets with decreasing citation information. We found that PageRank performs better than simple citation counts, but both algorithms are surprisingly robust to information loss. We conclude that even an incomplete citation database is likely to be effective for importance ranking.

Sleep quality and quantity and associated factors among high school students from south Texas

Background. Insufficient and poor quality sleep among adolescents affects not only the cognitive functioning, but overall health of the individual. Existing research suggests that adolescents from varying ethnic groups exhibit differing sleep patterns. However, little research focuses on sleep patterns and associated factors (i.e. tobacco use, mental health indicators) among Hispanic youth. ^ Methods. The study population (n=2,536) included students in grades 9-12 who attended one of the three public high schools along the Texas-Mexico border in 2003. This was a cross sectional study using secondary data collected via a web-based, confidential, self-administered survey. Separate logistic regression models were estimated to identify factors associated with reduced (<9 hours/night) and poor quality sleep on average during weeknights. ^ Results. Of participants, 49.5% reported reduced sleep while 12.8% reported poor quality sleep. Factors significantly (p<0.05) associated with poor quality sleep were: often feeling stressed or anxious (OR=5.49), being born in Mexico (OR=0.65), using a computer/playing video games 15+ hours per week (OR=2.29), working (OR=1.37), being a current smoker (OR=2.16), and being a current alcohol user (OR=1.64). Factors significantly associated with reduced quantity of sleep were: often feeling stressed or anxious (OR=2.74), often having headaches/stomachaches (OR=1.77), being a current marijuana user (OR=1.70), being a current methamphetamine user (OR=4.92), and being a current alcohol user (OR=1.27). ^ Discussion. Previous research suggests that there are several factors that can influence sleep quality and quantity in adolescents. This paper discusses these factors (i.e. work, smoking, alcohol, etc.) found to be associated with poor sleep quality and reduced sleep quantity in the Hispanic adolescent population. A reduced quantity of sleep (81.20% of the participants) and a poor quality of sleep (12.80% of the participants) were also found in high school students from South Texas. ^