Localization of adaptive variants in human genomes using averaged one-dependence estimation.

Statistical methods for identifying adaptive mutations from population genetic data face several obstacles: assessing the significance of genomic outliers, integrating correlated measures of selection into one analytic framework, and distinguishing adaptive variants from hitchhiking neutral variants. Here, we introduce SWIF(r), a probabilistic method that detects selective sweeps by learning the distributions of multiple selection statistics under different evolutionary scenarios and calculating the posterior probability of a sweep at each genomic site. SWIF(r) is trained using simulations from a user-specified demographic model and explicitly models the joint distributions of selection statistics, thereby increasing its power to both identify regions undergoing sweeps and localize adaptive mutations. Using array and exome data from 45 ‡Khomani San hunter-gatherers of southern Africa, we identify an enrichment of adaptive signals in genes associated with metabolism and obesity. SWIF(r) provides a transparent probabilistic framework for localizing beneficial mutations that is extensible to a variety of evolutionary scenarios

Colour by Numbers in Excel 2007: Solving Algebraic Equations Without Algebra

This is an update of an earlier paper, and is written for Excel 2007. A series of Excel 2007 models is described. The more advanced versions allow solution of f(x)=0 by examining change of sign of function values. The function is graphed and change of sign easily detected by a change of colour. Relevant features of Excel 2007 used are Names, Scatter Chart and Conditional Formatting. Several sample Excel 2007 models are available for download, and the paper is intended to be used as a lesson plan for students having some familiarity with derivatives. For comparison and reference purposes, the paper also presents a brief outline of several common equation-solving strategies as an Appendix

Enhancing student understanding of mathematical concepts through the development of estimation skills with the QAMA calculator

The development of learners’ conceptual understanding of mathematics (mathematical notions) constitutes one of the crucial problems in STEM disciplines (Byrnes & Wasik, 1991; Willingham, 2010; Richland et al., 2012). The overall aim of the project is to assist students with development of the above-mentioned capability by creating pedagogical environment that promotes students ‘deep learning (Marton & Säljö, 1976; Entwistle, 1981, 2000; Biggs, 1987, 1993; Ramsden, 1992; Simms 2006; Atherton, 2013). The authors will report on the progress so far with the pilot study investigating the ways of developing students’ understanding of mathematical concepts through the use of the QAMA scientific calculator (Samson, 2014). QAMA is a scientific calculator designed specifically to force the user to provide a “reasonable estimate” of the answer before giving any output. The authors re-designed the unit with the objective of creating educational experiences that assist students in becoming independent learners. The re-designed tasks required students to use the tool during a series of educational (collaborative) activities while learning the concept of mathematical estimation. The design of the task encouraged students to apply their previously acquired knowledge in the new situations, allowing them to perceive the connection between their freshly learnt estimation skills with application in new contexts. The re-designed unit, Mathematics for Exercise Science, a first-year mathematics unit for science students was introduced for the second semester of 2014 at Queensland University of Technology

Colour by Numbers: Solving Algebraic Equations Without Algebra

A series of Excel models is described. They allow solution of f(x) = 0 by examining change of sign of function values. The function is graphed and change of sign easily detected by a change of colour. Prominent Excel features used are Names, Chart Wizard and Conditional Formatting. Several sample Excel models are available for download, and the paper is intended to be used as a lesson plan for students having some familiarity with derivatives. For comparison and reference purposes, the paper also presents a brief outline of several common equation-solving strategies as an Appendix

The spreadsheet as a tool for teaching set theory: Part 1 – an Excel lesson plan to help solve Sudokus

This paper is intended to be used in the classroom. It describes essentially every step of the construction of an Excel model to help solve Sudoku puzzles. For those up to moderate difficulty, it will usually solve the puzzle to completion. For the more difficult ones, it still provides a platform for decision support. The paper may be found useful for a lesson in which students, who, having some basic knowledge of Excel, are learning some of its lesser-known features, such as conditional formatting. It also generates a useful tool for working with Sudoku puzzles, from the very easiest right up to the ones often labelled as fiendish or diabolical. Fundamental mathematical concepts such as set intersection, set partition and reduction of set partition to singletons are very graphically illustrated by the present Excel model for Sudoku. Prominent spreadsheet concepts presented here are conditional formatting, names, COUNTIF, CONCATENATE. The paper is accompanied by a completed Excel model, constructed by using the steps described herein. No VBA code is employed; the whole thing is done with Excel formulas and conditional formatting

Glycogen synthase kinases 3α and 3β in cardiac myocytes: regulation and consequences of their inhibition

Inhibition of glycogen synthase kinase 3β (GSK3β) as a consequence of its phosphorylation by protein kinase B/Akt (PKB/Akt) has been implicated in cardiac myocyte hypertrophy in response to endothelin-1 or phenylephrine. We examined the regulation of GSK3α (which we show to constitute a significant proportion of the myocyte GSK3 pool) and GSK3β in cardiac myocytes. Although endothelin increases phosphorylation of GSK3 and decreases its activity, the response is less than that induced by insulin (which does not promote cardiac myocyte hypertrophy). GSK3 phosphorylation induced by endothelin requires signalling through the extracellular signal-regulated kinase 1/2 (ERK1/2) cascade and not the PKB/Akt pathway, whereas the reverse is true for insulin. Cardiac myocyte hypertrophy involves changes in morphology, and in gene and protein expression. The potent GSK3 inhibitor 1-azakenpaullone increases myocyte area as a consequence of increased cell length whereas phenylephrine increases both length and width. Azakenpaullone or insulin promotes AP1 transcription factor binding to an AP1 consensus oligonucleotide, but this was significantly less than that induced by endothelin and derived principally from increased binding of JunB protein, the expression of which was increased. Azakenpaullone promotes significant changes in gene expression (assessed by Affymetrix microarrays), but the overall response is less than with endothelin and there is little overlap between the genes identified. Thus, although GSK3 may contribute to cardiac myocyte hypertrophy in some respects (and presumably plays an important role in myocyte metabolism), it does not appear to contribute as significantly to the response induced by endothelin as has been maintained

Basic Finance Made Accessible in Excel 2007: "The Big 5, Plus 2"

The basic principles and equations are developed for elementary finance, based on the concept of compound interest. The five quantities of interest in such problems are present value, future value, amount of periodic payment, number of periods and the rate of interest per period. We consider three distinct means of computing each of these five quantities in Excel 2007: (i) use of algebraic equations, (ii) by recursive schedule and the Goal Seek facility, and (iii) use of Excel's intrinsic financial functions. The paper is intended to be used as the basis for a lesson plan and contains many examples and solved problems. Comment is made regarding the relative difficulty of each approach, and a prominent theme is the systematic use of more than one method to increase student understanding and build confidence in the answer obtained. Full instructions to build each type of model are given and a complete set of examples and solutions may be downloaded (Examples.xlsx and Solutions.xlsx)