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Biochemistry, Biophysics, and Structural Biology Commons™
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Articles 1 - 5 of 5
Full-Text Articles in Biochemistry, Biophysics, and Structural Biology
Food Based Approaches For A Healthy Nutrition In Africa, Mamoudou Hama Dicko
Food Based Approaches For A Healthy Nutrition In Africa, Mamoudou Hama Dicko
Pr. Mamoudou H. DICKO, PhD
The latest estimates of the FAO demonstrate the problems of the fight against hunger. These problems are manifested by the ever-increasing number of chronically undernourished people worldwide. Their numbers during the 1999-2001 period were estimated at about 840 million of which 798 million live in developing countries. Sub-Saharan Africa alone represented 198 million of those. In this part of Africa the prevalence of undernourishment ranges from 5-34%, causing growth retardation and insufficient weight gain among one third of the children under five years of age and resulting in a mortality of 5-15% among these children. Malnutrition resulting from undernourishment is …
The C. Elegans Heterochronic Gene Lin-46 Affects Developmental Timing At Two Larval Stages And Encodes A Relative Of The Scaffolding Protein Gephyrin, A. S.-R. Pepper, Jill E. Mccane, Kevin Kemper, Dennis Au Yeung, Rosalind C. Lee, Victor Ambros, Eric G. Moss
The C. Elegans Heterochronic Gene Lin-46 Affects Developmental Timing At Two Larval Stages And Encodes A Relative Of The Scaffolding Protein Gephyrin, A. S.-R. Pepper, Jill E. Mccane, Kevin Kemper, Dennis Au Yeung, Rosalind C. Lee, Victor Ambros, Eric G. Moss
Dartmouth Scholarship
The succession of developmental events in the C. elegans larva is governed by the heterochronic genes. When mutated, these genes cause either precocious or retarded developmental phenotypes, in which stage-specific patterns of cell division and differentiation are either skipped or reiterated, respectively. We identified a new heterochronic gene, lin-46, from mutations that suppress the precocious phenotypes caused by mutations in the heterochronic genes lin-14 and lin-28. lin-46 mutants on their own display retarded phenotypes in which cell division patterns are reiterated and differentiation is prevented in certain cell lineages. Our analysis indicates that lin-46 acts at a step immediately downstream …
Mer1p Is A Modular Splicing Factor Whose Function Depends On The Conserved U2 Snrnp Protein Snu17p, Marc Spingola, Javier Armisen, Manuel Ares
Mer1p Is A Modular Splicing Factor Whose Function Depends On The Conserved U2 Snrnp Protein Snu17p, Marc Spingola, Javier Armisen, Manuel Ares
Biology Department Faculty Works
Mer1p activates the splicing of at least three pre‐mRNAs (AMA1, MER2, MER3) during meiosis in the yeast Saccharomyces cerevisiae. We demonstrate that enhancer recognition by Mer1p is separable from Mer1p splicing activation. The C‐terminal KH‐type RNA‐binding domain of Mer1p recognizes introns that contain the Mer1p splicing enhancer, while the N‐terminal domain interacts with the spliceosome and activates splicing. Prior studies have implicated the U1 snRNP and recognition of the 5′ splice site as key elements in Mer1p‐activated splicing. We provide new evidence that Mer1p may also function at later steps of spliceosome assembly. First, Mer1p can activate splicing of introns …
Mer1p Is A Modular Splicing Factor Whose Function Depends On The Conserved U2 Snrnp Protein Snu17p, Marc Spingola, Javier Armisen, Manuel Ares
Mer1p Is A Modular Splicing Factor Whose Function Depends On The Conserved U2 Snrnp Protein Snu17p, Marc Spingola, Javier Armisen, Manuel Ares
Marc Spingola
Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.
Computational Protein Biomarker Prediction: A Case Study For Prostate Cancer, Michael Wagner, Dayanand N. Naik, Alex Pothen, Srinivas Kasukurti, Raghu Ram Devineni, Bao-Ling Adam, O. John Semmes, George L. Wright Jr.
Mathematics & Statistics Faculty Publications
Background: Recent technological advances in mass spectrometry pose challenges in computational mathematics and statistics to process the mass spectral data into predictive models with clinical and biological significance. We discuss several classification-based approaches to finding protein biomarker candidates using protein profiles obtained via mass spectrometry, and we assess their statistical significance. Our overall goal is to implicate peaks that have a high likelihood of being biologically linked to a given disease state, and thus to narrow the search for biomarker candidates.
Results: Thorough cross-validation studies and randomization tests are performed on a prostate cancer dataset with over 300 patients, obtained …