OpenSciInfo

GenBioWiki is the student home page for the Genetics, Bioinformatics, and Computational Biology (GBCB) program at Virginia Tech. Bioinformatics and computational biology provide a research platform to acquire, manage, analyze, and display large amounts of data, which in turn catalyze a systems approach to understanding biological organisms, as well as making useful predictions about their behavior in response to environmental and other perturbations. Moreover, bioinformatics is the study of biological systems and large biological data sets using analytical methods borrowed from computer science, mathematics, statistics, and the physical sciences. This transdisciplinary approach to research requires graduates with extensive cross-cultural professional and technical training and provides ample employment opportunities for Ph.D. graduates. [1]

Existing studies on BitTorrent systems are single-torrent based, while more than 85% of all peers participate in multiple torrents according to our trace analysis. In addition, these studies are not sufficiently insightful and accurate even for single-torrent models, due to some unrealistic assumptions. Our analysis of representative BitTorrent traffic provides several new findings regarding the limitations of BitTorrent systems: (1) Due to the exponentially decreasing peer arrival rate in reality, service availability in such systems becomes poor quickly, after which it is difficult for the file to be located and downloaded. (2) Client performance in the BitTorrent-like systems is unstable, and fluctuates widely with the peer population. (3) Existing systems could provide unfair services to peers, where peers with high downloading speed tend to download more and upload less. In this paper, we study these limitations on torrent evolution in realistic environments. Motivated by the analysis and modeling results, we further build a graph based multi-torrent model to study inter-torrent collaboration. Our model quantitatively provides strong motivation for inter-torrent collaboration instead of directly stimulating seeds to stay longer. We also discuss a system design to show the feasibility of multi-torrent collaboration.

The Network for Open Scientific Innovation is founded upon the belief, no, the unshakeable certainty, that creativity, love, and intelligence can solve any problem. Recent years have seen technological revolutions in informatics, communications, and the life sciences. Sadly, this rapid progress has not been matched by a revolution in the democratization of scientific problem solving.

This FUSE-base VFS (Virtual FileSystem) enables all programs to look inside archived or compressed files, or access remote files without recompiling the programs or changing the kernel. At the moment it supports floppies, tar and gzip files, zip, bzip2, ar and rar files, ftp sessions, http, webdav, rsh/rcp, ssh/scp. Quite a few other handlers are implemented with the Midnight Commander's external FS.

In the page on Thoughs on institutional OER contributions I argue that (among other things) having a good export of material from shared resources (like the OER Toolkit or wikieducator) is important for getting institutions to contribute. How is this requirement met by the platform used for the OER Toolkit and wikieducator?

The establishment of open access literature makes it possible for knowledge to be extracted from scholarly articles and included in other resources. BioLit aims to extract database identifiers and rich meta-data from open access articles in the life sciences and integrate that information with existing biological databases. We have begun prototyping this effort using a clone of the RCSB Protein Data Bank, a database of macromolecular structures.

WikiGenes is the first wiki system to combine the collaborative and largely altruistic possibilities of wikis with explicit authorship. In view of the extraordinary success of Wikipedia there remains no doubt about the potential of collaborative publishing, yet its adoption in science has been limited. Here I discuss a dynamic collaborative knowledge base for the life sciences that provides authors with due credit and that can evolve via continual revision and traditional peer review into a rigorous scientific