The Online Bioinformatics Resources Collection at the University of Pittsburgh Health Sciences Library System—a one-stop gateway to online bioinformatics databases and software tools

To bridge the gap between the rising information needs of biological and medical researchers and the rapidly growing number of online bioinformatics resources, we have created the Online Bioinformatics Resources Collection (OBRC) at the Health Sciences Library System (HSLS) at the University of Pittsburgh. The OBRC, containing 1542 major online bioinformatics databases and software tools, was constructed using the HSLS content management system built on the Zope(®) Web application server. To enhance the output of search results, we further implemented the Vivísimo Clustering Engine(®), which automatically organizes the search results into categories created dynamically based on the textual information of the retrieved records. As the largest online collection of its kind and the only one with advanced search results clustering, OBRC is aimed at becoming a one-stop guided information gateway to the major bioinformatics databases and software tools on the Web. OBRC is available at the University of Pittsburgh's HSLS Web site ()

A Stable Cranial Neural Crest Cell Line from Mouse

Cranial neural crest cells give rise to ectomesenchymal derivatives such as cranial bones, cartilage, smooth muscle, dentin, as well as melanocytes, corneal endothelial cells, and neurons and glial cells of the peripheral nervous system. Previous studies have suggested that although multipotent stem-like cells may exist during the course of cranial neural crest development, they are transient, undergoing lineage restriction early in embryonic development. We have developed culture conditions that allow cranial neural crest cells to be grown as multipotent stem-like cells. With these methods, we obtained 2 independent cell lines, O9-1 and i10-1, which were derived from mass cultures of Wnt1-Cre; R26R-GFP-expressing cells. These cell lines can be propagated and passaged indefinitely, and can differentiate into osteoblasts, chondrocytes, smooth muscle cells, and glial cells. Whole-genome expression profiling of O9-1 cells revealed that this line stably expresses stem cell markers (CD44, Sca-1, and Bmi1) and neural crest markers (AP-2α, Twist1, Sox9, Myc, Ets1, Dlx1, Dlx2, Crabp1, Epha2, and Itgb1). O9-1 cells are capable of contributing to cranial mesenchymal (osteoblast and smooth muscle) neural crest fates when injected into E13.5 mouse cranial tissue explants and chicken embryos. These results suggest that O9-1 cells represent multipotent mesenchymal cranial neural crest cells. The O9-1 cell line should serve as a useful tool for investigating the molecular properties of differentiating cranial neural crest cells

Statistical Origin of Constituent-Quark Scaling in the QGP hadronization

Nonextensive statistics in a Blast-Wave model (TBW) is implemented to describe the identified hadron production in relativistic p+p and nucleus-nucleus collisions. Incorporating the core and corona components within the TBW formalism allows us to describe simultaneously some of the major observations in hadronic observables at the Relativistic Heavy-Ion Collider (RHIC): the Number of Constituent Quark Scaling (NCQ), the large radial and elliptic flow, the effect of gluon saturation and the suppression of hadron production at high transverse momentum (pT) due to jet quenching. In this formalism, the NCQ scaling at RHIC appears as a consequence of non-equilibrium process. Our study also provides concise reference distributions with a least chi2 fit of the available experimental data for future experiments and models.Comment: 4 pages, 3 figures; added two tables, explained a little bit more on TBW_p

NONCODE: an integrated knowledge database of non-coding RNAs

NONCODE is an integrated knowledge database dedicated to non-coding RNAs (ncRNAs), that is to say, RNAs that function without being translated into proteins. All ncRNAs in NONCODE were filtered automatically from literature and GenBank, and were later manually curated. The distinctive features of NONCODE are as follows: (i) the ncRNAs in NONCODE include almost all the types of ncRNAs, except transfer RNAs and ribosomal RNAs. (ii) All ncRNA sequences and their related information (e.g. function, cellular role, cellular location, chromosomal information, etc.) in NONCODE have been confirmed manually by consulting relevant literature: more than 80% of the entries are based on experimental data. (iii) Based on the cellular process and function, which a given ncRNA is involved in, we introduced a novel classification system, labeled process function class, to integrate existing classification systems. (iv) In addition, some 1100 ncRNAs have been grouped into nine other classes according to whether they are specific to gender or tissue or associated with tumors and diseases, etc. (v) NONCODE provides a user-friendly interface, a visualization platform and a convenient search option, allowing efficient recovery of sequence, regulatory elements in the flanking sequences, secondary structure, related publications and other information. The first release of NONCODE (v1.0) contains 5339 non-redundant sequences from 861 organisms, including eukaryotes, eubacteria, archaebacteria, virus and viroids. Access is free for all users through a web interface at http://noncode.bioinfo.org.cn