Daniel Scanfeld

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BACKGROUND This study reviewed Twitter status updates mentioning "antibiotic(s)" to determine overarching categories and explore evidence of misunderstanding or misuse of antibiotics. METHODS One thousand Twitter status updates mentioning antibiotic(s) were randomly selected for content analysis and categorization. To explore cases of potential(More)
Infection with the malaria parasite Plasmodium falciparum leads to widely different clinical conditions in children, ranging from mild flu-like symptoms to coma and death. Despite the immense medical implications, the genetic and molecular basis of this diversity remains largely unknown. Studies of in vitro gene expression have found few transcriptional(More)
The high dimensionality of global transcription profiles, the expression level of 20,000 genes in a much small number of samples, presents challenges that affect the sensitivity and general applicability of analysis results. In principle, it would be better to describe the data in terms of a small number of metagenes, positive linear combinations of genes,(More)
Gene expression analysis has identified biologically relevant subclasses of breast cancer. However, most classification schemes do not robustly cluster all HER2+ breast cancers, in part due to limitations and bias of clustering techniques used. In this article, we propose an alternative approach that first separates the HER2+ tumors using a gene(More)
Artemisinin-based combination therapies (ACTs) are highly effective for the treatment of Plasmodium falciparum malaria, yet their sustained efficacy is threatened by the potential spread of parasite resistance. Recent studies have provided evidence that artemisinins can inhibit the function of PfATP6, the P. falciparum ortholog of the ER calcium pump SERCA,(More)
Clustering analysis of microarray data is often criticized for giving ambiguous results because of sensitivity to data perturbation or clustering techniques used. In this paper, we describe a new method based on principal component analysis and ensemble consensus clustering that avoids these problems. We illustrate the method on a public microarray dataset(More)
A central problem in biology is to identify gene function. One approach is to infer function in large supergenomic networks of interactions and ancestral relationships among genes; however, their analysis can be computationally prohibitive. We show here that these biological networks are compressible. They can be shrunk dramatically by eliminating redundant(More)
We describe a new method based on principal component analysis and robust consensus ensemble clustering to identify and elucidate the subtypes of breast cancer disease. The method was applied to microarray gene expression data using micro-dissection of samples from 36 breast cancer patients with at least two of three pathological stages of disease. Controls(More)
The acquisition of multidrug resistance by Plasmodium falciparum underscores the need to understand the underlying molecular mechanisms so as to counter their impact on malaria control. For the many antimalarials whose mode of action relates to inhibition of heme detoxification inside infected erythrocytes, the digestive vacuole transporters PfCRT and(More)
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