Molecular Biomechanics: The Molecular Basis of How Forces Regulate Cellular Function

Recent advances have led to the emergence of molecular biomechanics as an essential element of modern biology. These efforts focus on theoretical and experimental studies of the mechanics of proteins and nucleic acids, and the understanding of the molecular mechanisms of stress transmission, mechanosensing and mechanotransduction in living cells. In particular, single-molecule biomechanics studies of proteins and DNA, and mechanochemical coupling in biomolecular motors have demonstrated the critical importance of molecular mechanics as a new frontier in bioengineering and life sciences. To stimulate a more systematic study of the basic issues in molecular biomechanics, and attract a broader range of researchers to enter this emerging field, here we discuss its significance and relevance, describe the important issues to be addressed and the most critical questions to be answered, summarize both experimental and theoretical/computational challenges, and identify some short-term and long-term goals for the field. The needs to train young researchers in molecular biomechanics with a broader knowledge base, and to bridge and integrate molecular, subcellular and cellular level studies of biomechanics are articulated.National Institutes of Health (U.S.) (grant UO1HL80711-05 to GB)National Institutes of Health (U.S.) (grant R01GM076689-01)National Institutes of Health (U.S.) (grant R01AR033236-26)National Institutes of Health (U.S.) (grant R01GM087677-01A1)National Institutes of Health (U.S.) (grant R01AI44902)National Institutes of Health (U.S.) (grant R01AI38282)National Science Foundation (U.S.) (grant CMMI-0645054)National Science Foundation (U.S.) (grant CBET-0829205)National Science Foundation (U.S.) (grant CAREER-0955291

OPSitu:A Semantic-Web Based Situation Inference Tool Under Opportunistic Sensing Paradigm

Opportunistic sensing becomes a competitive sensing paradigm nowadays. Instead of pre-deploying application-specific sensors, it makes use of sensors that just happen to be available to accomplish its sensing goal. In the opportunistic sensing paradigm, the sensors that can be utilized by a given application in a given time are unpredictable. This brings the Semantic-Web based situation inference approach, which is widely adopted in situation-aware applications, a major challenge, i.e., how to handle uncertainty of the availability and confidence of the sensing data. Although extending standard semantic-web languages may enable the situation inference to be compatible with the uncertainty, it also brings extra complexity to the languages and makes them hard to be learned. Unlike the existing works, this paper developed a situation inference tool, named OPSitu, which enables the situation inference rules to be written in the well accepted standard languages such as OWL and SWRL even under opportunistic sensing paradigm. An experiment is also described to demonstrate the validity of OPSitu