Is protein folding problem really a NP-complete one ? First investigations

To determine the 3D conformation of proteins is a necessity to understand their functions or interactions with other molecules. It is commonly admitted that, when proteins fold from their primary linear structures to their final 3D conformations, they tend to choose the ones that minimize their free energy. To find the 3D conformation of a protein knowing its amino acid sequence, bioinformaticians use various models of different resolutions and artificial intelligence tools, as the protein folding prediction problem is a NP complete one. More precisely, to determine the backbone structure of the protein using the low resolution models (2D HP square and 3D HP cubic), by finding the conformation that minimize free energy, is intractable exactly. Both the proof of NP-completeness and the 2D prediction consider that acceptable conformations have to satisfy a self-avoiding walk (SAW) requirement, as two different amino acids cannot occupy a same position in the lattice. It is shown in this document that the SAW requirement considered when proving NP-completeness is different from the SAW requirement used in various prediction programs, and that they are different from the real biological requirement. Indeed, the proof of NP completeness and the predictions in silico consider conformations that are not possible in practice. Consequences of this fact are investigated in this research work.Comment: Submitted to Journal of Bioinformatics and Computational Biology, under revie

Dissecting the Ethical Brain

Evolution through natural selection has endowed our species with the innate capacity to process information by the use of our brains. Through natural gene selection, our ability to process this information varies from individual to individual. What if the genome dictating the variation of an individual’s intellect, athletic ability, or even personality, can be enhanced by pharmaceuticals or brain therapy? How can we differentiate between an embryo and human life? When do powerful brain imaging technologies, that can literally “read” you brain, cross the abstract line of an individual’s privacy and right to self? How do we diffuse the gray cloud that surrounds ethics today? Michael S. Gazzaniga, an outspoken member of the President’s Council on Bioethics, may not have all the answers, but he provides much insight in his critically acclaimed book, The Ethical Brain. This thrilling eye-opener helps us debunk many medical ethical dilemmas our society has come to face in recent years with insightful developments in the field of neuroscience... The Ethical Brain is a lively confrontational and thought-provoking book about the world of neuroethics and its solutions to numerous social problems. Gazzaniga illuminates scientific findings in this enjoyable read in hopes that it will write a new page in the understanding of bioethics. After reading the book, one walks away with not only academic merit but with a greater sense of self. This father of cognitive science will have you basking in his fruit of enjoyable scientific discovery and understanding

PARSEC vs. SPLASH-2: A quantitative comparison of two multithreaded benchmark suites on Chip-Multiprocessors

The PARSEC benchmark suite was recently released and has been adopted by a significant number of users within a short amount of time. This new collection of workloads is not yet fully under-stood by researchers. In this study we compare the SPLASH-2 and PARSEC benchmark suites with each other to gain insights into differences and similarities between the two program collections. We use standard statistical methods and machine learning to ana-lyze the suites for redundancy and overlap on Chip-Multiprocessors (CMPs). Our analysis shows that PARSEC workloads are funda-mentally different from SPLASH-2 benchmarks. The observed dif-ferences can be explained with two technology trends, the prolifer-ation of CMPs and the accelerating growth of world data

Reconfigurable Modular Mobile Robotic Platform (ReMMRP)

This project addresses the inflexibility of modern robotics by developing a modular robotic platform, capable of using various modules that can be added and removed to a base unit in a short amount of time. The scope of the project limited development of modules to a 3-DOF leg. The proof of concept was established by developing a main communications board capable of detecting attached peripherals, and individual leg circuit boards capable of full PID control utilizing inverse kinematics to precisely place the end of the leg. Mechanical issues prevented the leg constructed from being fully functional, however plans have been developed to address all issues found in the development of this platform