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5 result(s) for 'sanders' within Volume 12 of BMC Bioinformatics

1. ss-TEA: Entropy based identification of receptor specific ligand binding residues from a multiple sequence alignment of class A GPCRs

   G-protein coupled receptors (GPCRs) are involved in many different physiological processes and their function can be modulated by small molecules which bind in the transmembrane (TM) domain. Because of their s...

   Authors: Marijn PA Sanders, Wilco WM Fleuren, Stefan Verhoeven, Sven van den Beld, Wynand Alkema, Jacob de Vlieg and Jan PG Klomp

   Citation: BMC Bioinformatics 2011 12:332

   Content type: Research article Published on: 10 August 2011

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2. The Proteogenomic Mapping Tool

   High-throughput mass spectrometry (MS) proteomics data is increasingly being used to complement traditional structural genome annotation methods. To keep pace with the high speed of experimental data generatio...

   Authors: William S Sanders, Nan Wang, Susan M Bridges, Brandon M Malone, Yoginder S Dandass, Fiona M McCarthy, Bindu Nanduri, Mark L Lawrence and Shane C Burgess

   Citation: BMC Bioinformatics 2011 12:115

   Content type: Software Published on: 22 April 2011

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3. Hsp90/Cdc37 Chaperone/co-chaperone complex, a novel junction anticancer target elucidated by the mode of action of herbal drug Withaferin A

   HSPs (Heat shock proteins) are highly conserved ubiquitous proteins among species which are involved in maintaining appropriate folding and conformation of other proteins and are thus referred to as molecular ...

   Authors: Abhinav Grover, Ashutosh Shandilya, Vibhuti Agrawal, Piyush Pratik, Divya Bhasme, Virendra S Bisaria and Durai Sundar

   Citation: BMC Bioinformatics 2011 12(Suppl 1):S30

   Content type: Research Published on: 15 February 2011

   This article is part of a Supplement: Volume 12 Supplement 1

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4. Predicting and analyzing DNA-binding domains using a systematic approach to identifying a set of informative physicochemical and biochemical properties

   Existing methods of predicting DNA-binding proteins used valuable features of physicochemical properties to design support vector machine (SVM) based classifiers. Generally, selection of physicochemical proper...

   Authors: Hui-Lin Huang, I-Che Lin, Yi-Fan Liou, Chia-Ta Tsai, Kai-Ti Hsu, Wen-Lin Huang, Shinn-Jang Ho and Shinn-Ying Ho

   Citation: BMC Bioinformatics 2011 12(Suppl 1):S47

   Content type: Research Published on: 15 February 2011

   This article is part of a Supplement: Volume 12 Supplement 1

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5. HemeBIND: a novel method for heme binding residue prediction by combining structural and sequence information

   Accurate prediction of binding residues involved in the interactions between proteins and small ligands is one of the major challenges in structural bioinformatics. Heme is an essential and commonly used ligan...

   Authors: Rong Liu and Jianjun Hu

   Citation: BMC Bioinformatics 2011 12:207

   Content type: Research article Published on: 26 May 2011

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