The Adventures of Little Oyster, revised edition

First published in 1955

Let\u27s Be Oyster Farmers

First published in 1958

Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data

A major goal of molecular biology is determining the mechanisms that control the transcription of genes. Motif Enrichment Analysis (MEA) seeks to determine which DNA-binding transcription factors control the transcription of a set of genes by detecting enrichment of known binding motifs in the genes' regulatory regions. Typically, the biologist specifies a set of genes believed to be co-regulated and a library of known DNA-binding models for transcription factors, and MEA determines which (if any) of the factors may be direct regulators of the genes. Since the number of factors with known DNA-binding models is rapidly increasing as a result of high-throughput technologies, MEA is becoming increasingly useful. In this paper, we explore ways to make MEA applicable in more settings, and evaluate the efficacy of a number of MEA approaches.We first define a mathematical framework for Motif Enrichment Analysis that relaxes the requirement that the biologist input a selected set of genes. Instead, the input consists of all regulatory regions, each labeled with the level of a biological signal. We then define and implement a number of motif enrichment analysis methods. Some of these methods require a user-specified signal threshold, some identify an optimum threshold in a data-driven way and two of our methods are threshold-free. We evaluate these methods, along with two existing methods (Clover and PASTAA), using yeast ChIP-chip data. Our novel threshold-free method based on linear regression performs best in our evaluation, followed by the data-driven PASTAA algorithm. The Clover algorithm performs as well as PASTAA if the user-specified threshold is chosen optimally. Data-driven methods based on three statistical tests-Fisher Exact Test, rank-sum test, and multi-hypergeometric test--perform poorly, even when the threshold is chosen optimally. These methods (and Clover) perform even worse when unrestricted data-driven threshold determination is used.Our novel, threshold-free linear regression method works well on ChIP-chip data. Methods using data-driven threshold determination can perform poorly unless the range of thresholds is limited a priori. The limits implemented in PASTAA, however, appear to be well-chosen. Our novel algorithms--AME (Analysis of Motif Enrichment)-are available at http://bioinformatics.org.au/ame/

Generalized packing designs

Generalized $t$-designs, which form a common generalization of objects such as $t$-designs, resolvable designs and orthogonal arrays, were defined by Cameron [P.J. Cameron, A generalisation of $t$-designs, \emph{Discrete Math.}\ {\bf 309} (2009), 4835--4842]. In this paper, we define a related class of combinatorial designs which simultaneously generalize packing designs and packing arrays. We describe the sometimes surprising connections which these generalized designs have with various known classes of combinatorial designs, including Howell designs, partial Latin squares and several classes of triple systems, and also concepts such as resolvability and block colouring of ordinary designs and packings, and orthogonal resolutions and colourings. Moreover, we derive bounds on the size of a generalized packing design and construct optimal generalized packings in certain cases. In particular, we provide methods for constructing maximum generalized packings with $t=2$ and block size $k=3$ or 4.Comment: 38 pages, 2 figures, 5 tables, 2 appendices. Presented at 23rd British Combinatorial Conference, July 201

Development of an Unmanned Aerial Vehicle for the Measurement of Turbulence in the Atmospheric Boundary Layer

This paper describes the components and usage of an unmanned aerial vehicle developed for measuring turbulence in the atmospheric boundary layer. A method of computing the time-dependent wind speed from a moving velocity sensor data is provided. The physical system built to implement this method using a five-hole probe velocity sensor is described along with the approach used to combine data from the different on-board sensors to allow for extraction of the wind speed as a function of time and position. The approach is demonstrated using data from three flights of two unmanned aerial vehicles (UAVs) measuring the lower atmospheric boundary layer during transition from a stable to convective state. Several quantities are presented and show the potential for extracting a range of atmospheric boundary layer statistics

ISSLS PRIZE IN BIOENGINEERING SCIENCE 2019: biomechanical changes in dynamic sagittal balance and lower limb compensatory strategies following realignment surgery in adult spinal deformity patients.

Study designA longitudinal cohort study.ObjectiveTo define a set of objective biomechanical metrics that are representative of adult spinal deformity (ASD) post-surgical outcomes and that may forecast post-surgical mechanical complications. Current outcomes for ASD surgical planning and post-surgical assessment are limited to static radiographic alignment and patient-reported questionnaires. Little is known about the compensatory biomechanical strategies for stabilizing sagittal balance during functional movements in ASD patients.MethodsWe collected in-clinic motion data from 15 ASD patients and 10 controls during an unassisted sit-to-stand (STS) functional maneuver. Joint motions were measured using noninvasive 3D depth mapping sensor technology. Mathematical methods were used to attain high-fidelity joint-position tracking for biomechanical modeling. This approach provided reliable measurements for biomechanical behaviors at the spine, hip, and knee. These included peak sagittal vertical axis (SVA) over the course of the STS, as well as forces and muscular moments at various joints. We compared changes in dynamic sagittal balance (DSB) metrics between pre- and post-surgery and then separately compared pre- and post-surgical data to controls.ResultsStandard radiographic and patient-reported outcomes significantly improved following realignment surgery. From the DSB biomechanical metrics, peak SVA and biomechanical loads and muscular forces on the lower lumbar spine significantly reduced following surgery (- 19 to - 30%, all p < 0.05). In addition, as SVA improved, hip moments decreased (- 28 to - 65%, all p < 0.05) and knee moments increased (+ 7 to + 28%, p < 0.05), indicating changes in lower limb compensatory strategies. After surgery, DSB data approached values from the controls, with some post-surgical metrics becoming statistically equivalent to controls.ConclusionsLongitudinal changes in DSB following successful multi-level spinal realignment indicate reduced forces on the lower lumbar spine along with altered lower limb dynamics matching that of controls. Inadequate improvement in DSB may indicate increased risk of post-surgical mechanical failure. These slides can be retrieved under Electronic Supplementary Material