Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Life Sciences
A Quick Guide For Building A Successful Bioinformatics Community., Aidan Budd, Manuel Corpas, Michelle D Brazas, Jonathan C Fuller, Jeremy Goecks, Nicola J Mulder, Magali Michaut, B F Francis Ouellette, Aleksandra Pawlik, Niklas Blomberg
A Quick Guide For Building A Successful Bioinformatics Community., Aidan Budd, Manuel Corpas, Michelle D Brazas, Jonathan C Fuller, Jeremy Goecks, Nicola J Mulder, Magali Michaut, B F Francis Ouellette, Aleksandra Pawlik, Niklas Blomberg
Computational Biology Institute
"Scientific community" refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding …
Trail-Based High Throughput Screening Reveals A Link Between Trail-Mediated Apoptosis And Glutathione Reductase, A Key Component Of Oxidative Stress Response., Dmitri Rozanov, Anton Cheltsov, Eduard Sergienko, Stefan Vasile, Vladislav Golubkov, Alexander E Aleshin, Trevor Levin, Elie Traer, Byron Hann, Julia Freimuth, Nikita Alexeev, Max A Alekseyev, Sergey P Budko, Hans Peter Bächinger, Paul Spellman
Trail-Based High Throughput Screening Reveals A Link Between Trail-Mediated Apoptosis And Glutathione Reductase, A Key Component Of Oxidative Stress Response., Dmitri Rozanov, Anton Cheltsov, Eduard Sergienko, Stefan Vasile, Vladislav Golubkov, Alexander E Aleshin, Trevor Levin, Elie Traer, Byron Hann, Julia Freimuth, Nikita Alexeev, Max A Alekseyev, Sergey P Budko, Hans Peter Bächinger, Paul Spellman
Computational Biology Institute
A high throughput screen for compounds that induce TRAIL-mediated apoptosis identified ML100 as an active chemical probe, which potentiated TRAIL activity in prostate carcinoma PPC-1 and melanoma MDA-MB-435 cells. Follow-up in silico modeling and profiling in cell-based assays allowed us to identify NSC130362, pharmacophore analog of ML100 that induced 65-95% cytotoxicity in cancer cells and did not affect the viability of human primary hepatocytes. In agreement with the activation of the apoptotic pathway, both ML100 and NSC130362 synergistically with TRAIL induced caspase-3/7 activity in MDA-MB-435 cells. Subsequent affinity chromatography and inhibition studies convincingly demonstrated that glutathione reductase (GSR), a key …
Pathoscope: Species Identification And Strain Attribution With Unassembled Sequencing Data., Owen E Francis, Matthew Bendall, Solaiappan Manimaran, Changjin Hong, Nathan L Clement, Eduardo Castro-Nallar, Quinn Snell, G Bruce Schaalje, Mark J Clement, Keith A Crandall, W Evan Johnson
Pathoscope: Species Identification And Strain Attribution With Unassembled Sequencing Data., Owen E Francis, Matthew Bendall, Solaiappan Manimaran, Changjin Hong, Nathan L Clement, Eduardo Castro-Nallar, Quinn Snell, G Bruce Schaalje, Mark J Clement, Keith A Crandall, W Evan Johnson
Computational Biology Institute
Emerging next-generation sequencing technologies have revolutionized the collection of genomic data for applications in bioforensics, biosurveillance, and for use in clinical settings. However, to make the most of these new data, new methodology needs to be developed that can accommodate large volumes of genetic data in a computationally efficient manner. We present a statistical framework to analyze raw next-generation sequence reads from purified or mixed environmental or targeted infected tissue samples for rapid species identification and strain attribution against a robust database of known biological agents. Our method, Pathoscope, capitalizes on a Bayesian statistical framework that accommodates information on sequence …
A Genomic Island In Salmonella Enterica Ssp. Salamae Provides New Insights On The Genealogy Of The Locus Of Enterocyte Effacement., P Scott Chandry, Simon Gladman, Sean C Moore, Torsten Seemann, Keith A Crandall, Narelle Fegan
A Genomic Island In Salmonella Enterica Ssp. Salamae Provides New Insights On The Genealogy Of The Locus Of Enterocyte Effacement., P Scott Chandry, Simon Gladman, Sean C Moore, Torsten Seemann, Keith A Crandall, Narelle Fegan
Computational Biology Institute
The genomic island encoding the locus of enterocyte effacement (LEE) is an important virulence factor of the human pathogenic Escherichia coli. LEE typically encodes a type III secretion system (T3SS) and secreted effectors capable of forming attaching and effacing lesions. Although prominent in the pathogenic E. coli such as serotype O157:H7, LEE has also been detected in Citrobacter rodentium, E. albertii, and although not confirmed, it is likely to also be in Shigella boydii. Previous phylogenetic analysis of LEE indicated the genomic island was evolving through stepwise acquisition of various components. This study describes a new LEE region from two …