Robustness and modular design of the Drosophila segment polarity network

Biomolecular networks have to perform their functions robustly. A robust function may have preferences in the topological structures of the underlying network. We carried out an exhaustive computational analysis on network topologies in relation to a patterning function in Drosophila embryogenesis. We found that while the vast majority of topologies can either not perform the required function or only do so very fragilely, a small fraction of topologies emerges as particularly robust for the function. The topology adopted by Drosophila, that of the segment polarity network, is a top ranking one among all topologies with no direct autoregulation. Furthermore, we found that all robust topologies are modular--each being a combination of three kinds of modules. These modules can be traced back to three sub-functions of the patterning function and their combinations provide a combinatorial variability for the robust topologies. Our results suggest that the requirement of functional robustness drastically reduces the choices of viable topology to a limited set of modular combinations among which nature optimizes its choice under evolutionary and other biological constraints.Comment: Supplementary Information and Synopsis available at http://www.ucsf.edu/tanglab

A sign on a tree: A case for “public knowledge”

Can information be objective and/or subjective? Based on Patrick Wilson’s notion of public knowledge and a story of a sign on a tree, this paper argues that private information is not the same as subjective information, and that the very communicative process of making information makes information objective. It also argues that the objective sense of information—public knowledge—has been and will be most relevant to information science, hence questions concerning collective responsibility in collecting, preserving, and organizing information shall be considered

An Implementation of Performance-Based Funding System At Individual Level: An Explorative Study

Performance-based funding systems are designed to encourage research and innovation. These systems have been implemented in many countries at aggregated level. A university in the Republic of Ireland has recently adopted the Norwegian/Danish model and implemented it at individual level. This study aims to understand the impact of this implementation on research practices, including, but not limited to, choice of publication channels and local and international collaboration, as well as the perception and evaluation of the funding scheme with regard to transparency and objectivity

Planning for impact – a framework for achievable impacts in grant applications and impact statements.

Grant applications and impact statements for research projects are important points for researchers and assessors to consider the future impact of research and whether the proposed pathways to these goals are feasible. Drawing on evidence from REF2014 impact case studies, Lai Ma provides a framework for achievable impacts that can help both researchers and assessors in determining how their work can lead to different impacts and outcomes

Automatic domain ontology extraction for context-sensitive opinion mining

Automated analysis of the sentiments presented in online consumer feedbacks can facilitate both organizations’ business strategy development and individual consumers’ comparison shopping. Nevertheless, existing opinion mining methods either adopt a context-free sentiment classification approach or rely on a large number of manually annotated training examples to perform context sensitive sentiment classification. Guided by the design science research methodology, we illustrate the design, development, and evaluation of a novel fuzzy domain ontology based contextsensitive opinion mining system. Our novel ontology extraction mechanism underpinned by a variant of Kullback-Leibler divergence can automatically acquire contextual sentiment knowledge across various product domains to improve the sentiment analysis processes. Evaluated based on a benchmark dataset and real consumer reviews collected from Amazon.com, our system shows remarkable performance improvement over the context-free baseline