자연주의적 탐구조사(Naturalistic Inquiry)

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Using Multivariate Statistics

Co-Planar Stereotaxic Atlas of the Human Brain—3-Dimensional Proportional System: An Approach to Cerebral Imaging, J. Talairach, P. Tournoux. Georg Thieme Verlag, New York (1988), 122 pp., 130 figs. DM 268

Data Mining Practical Machine Learning Tools and Techniques

Preamble and Transition to ACC/AHA Guidelines to Reduce Cardiovascular Risk S2

The goals of the …

/pdf/2013-acc-aha-guideline-on-the-treatment-of-blood-cholesterol-pvngcav7fq.pdf

2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines

Clinical Characteristics and Outcomes of Cryoballoon Pulmonary Vein Isolation for Atrial Fibrillation: Contemporary Results of the Auckland Regional Arrhythmia Service

L'invention porte sur de nouvelles regions charpentes humaines a chaine variable et sur des anticorps humanises comprenant lesdites regions. L'invention porte egalement sur un nouveau procede d'identification de regions charpentes acceptrices dans des sequences d'accepteurs, recourant a une retromutation pour greffer une sequence donneuse sur une charpente humaine.

Greffage par specificite d'un anticorps murin sur une charpente humaine

The application of latent variable modeling in various areas of psychological research has dramatically grown in popularity over the past three decades (see e.g., Breckler, 1990; Hershberger, 2003; MacCallum & Austin, 2000; Tomarken & Waller, 2005; Tremblay & Gardner, 1996 for systematic reviews). This growth is also apparent in educational psychology research that primarily seeks to address a range of applied and policy related questions to promote educational outcomes.

Latent Variable Modeling in Educational Psychology

Motivation: Binding of transcription factors to transcription factor binding sites (TFBSs) is key to the mediation of transcriptional regulation. Information on experimentally validated functional TFBSs is limited and consequently there is a need for accurate prediction of TFBSs both for gene annotation and in applications such as evaluating the effects of single nucleotide variations in causing disease. TFBSs are recognized by scanning a position weight matrix (PWM) against DNA using one of a number of computer programs. Thus we set out to create improved PWMs and to evaluate the performance of different programs. Results: We generated a new set of PWMs using de novo motif discovery based on ChIP-Seq data and showed that these considerably outperform PWMs derived from SELEX or individual promoter assays obtained from the JASPAR database. TFBS prediction tools fall into two classes — those that predict individual TFBSs and those that identify clusters. FIMO and MCAST performed best respectively. Availability and Implementation: The matrices are available to download as a ZIP file or gzipped tar file from http://www. bioinf.org.uk/tfbs/. This web site also allows the matrices to be browsed, viewed as ‘sequence logos’ and downloaded individually.

/pdf/optimizing-the-prediction-of-transcription-factor-binding-3jhkd7p17s.pdf

Andrew J. Martin

Papers

Clinical Characteristics and Outcomes of Cryoballoon Pulmonary Vein Isolation for Atrial Fibrillation: Contemporary Results of the Auckland Regional Arrhythmia Service

Greffage par specificite d'un anticorps murin sur une charpente humaine

Latent Variable Modeling in Educational Psychology

Optimizing the Prediction of Transcription Factor Binding Sites

The project’s research methods: addressing gaps in previous arts research