Structural Analysis of Polarizing Indels Argues the Root of the Tree of Life is Near the Chloroflexi

Determining which branches of the tree of life have derived features narrows down the possible location of the root. Currently the polarization of indels done by Lake _et al_.^1-5^ and the polarizing transitions of Cavalier-Smith^6^ arrive at contradictory positions for the root of the tree. We have analyzed the sequence based indel arguments using protein structure wherever possible. Structure strongly supports some of the polarizations, but in other indels it argues for a different conclusion. We conclude that there is no contradiction between Lake _et al_. and Cavalier-Smith; the root of the tree of life must be near the Chloroflexi.
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Application of protein structure alignments to iterated hidden Markov model protocols for structure prediction.

BackgroundOne of the most powerful methods for the prediction of protein structure from sequence information alone is the iterative construction of profile-type models. Because profiles are built from sequence alignments, the sequences included in the alignment and the method used to align them will be important to the sensitivity of the resulting profile. The inclusion of highly diverse sequences will presumably produce a more powerful profile, but distantly related sequences can be difficult to align accurately using only sequence information. Therefore, it would be expected that the use of protein structure alignments to improve the selection and alignment of diverse sequence homologs might yield improved profiles. However, the actual utility of such an approach has remained unclear.ResultsWe explored several iterative protocols for the generation of profile hidden Markov models. These protocols were tailored to allow the inclusion of protein structure alignments in the process, and were used for large-scale creation and benchmarking of structure alignment-enhanced models. We found that models using structure alignments did not provide an overall improvement over sequence-only models for superfamily-level structure predictions. However, the results also revealed that the structure alignment-enhanced models were complimentary to the sequence-only models, particularly at the edge of the "twilight zone". When the two sets of models were combined, they provided improved results over sequence-only models alone. In addition, we found that the beneficial effects of the structure alignment-enhanced models could not be realized if the structure-based alignments were replaced with sequence-based alignments. Our experiments with different iterative protocols for sequence-only models also suggested that simple protocol modifications were unable to yield equivalent improvements to those provided by the structure alignment-enhanced models. Finally, we found that models using structure alignments provided fold-level structure assignments that were superior to those produced by sequence-only models.ConclusionWhen attempting to predict the structure of remote homologs, we advocate a combined approach in which both traditional models and models incorporating structure alignments are used

Ten Simple Rules for Making Good Oral Presentations

1 documento en pdf de 174 páginas.El presente proyecto describió los cambios, avances, y transformaciones que generó el diseño y la implementación de un ambiente de aprendizaje mediado por TIC en la segmentación analítica que es un nivel de desarrollo de pensamiento y a la exposición oral de los estudiantes de grado sexto jornada mañana, Colegio Paraíso Mirador, sede C, localidad Ciudad Bolívar, Bogotá D. C, Colombia. La muestra del proyecto fue por conveniencia, no probabilística y presentó 37 estudiantes (21 hombres y 16 mujeres) del curso 602. El tipo de estudio del proyecto fue cualitativo-descriptivo, estudio de caso. La fundamentación pedagógica se basó en el aprendizaje significativo aunque también presentó algunos elementos conductistas y constructivistas. El ambiente de aprendizaje TIC influyó fortaleciendo la fluidez oral, el discurso y la coherencia en las exposiciones; por otra parte, identificó aspectos a mejorar como la pronunciación, voz baja, vocabulario, inferencia de términos especializados, cortesía comunicativa, escucha, atención, prudencia, particularización de herramientas y detalles comunicativos fonológicos importantes; también influyó a nivel científico fortaleciendo analíticamente el pensamiento de los educandos

Data Science @ the NIH: What is Happening & What is Coming: A Conversation

Philip E. Bourne, PhD, FACMI, is Associate Director for Data Science, National Institutes of Health. In his keynote presentation, he spoke on how the National Institutes of Health (NIH) is meeting the challenges of the scientific data explosion and the NIH\u27s future plans in this area