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The Power Decoder simulator for the evaluation of pooled shRNA screen performance
Jesse Stombaugh, Abel Licon, Žaklina Strezoska, Joshua Stahl, Sarah Bael Anderson, Michael Banos, Anja van Brabant Smith, Amanda Birmingham, Annaleen Vermeulen

Power Decoder (written in R and Python) simulates shRNA pooled screening experiments in silico to allow for the estimation of a screen’s statistical power. Populations of shRNAs were engineered in such a way that the magnitude of depletion and enrichment was known, then using the negative binomial distribution, an in silico model was developed to successfully resemble data from an actual laboratory experiment.

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Knockdown of long noncoding RNAs in breast cancer
1 Jennii Luu, 2 Jesper Maag, 1 Yanny Handoko, 3 Richard Redvers, 3,4 Robin L. Anderson, 5 Maren M. Gross , 2 Marcel E. Dinger, and 1,3 Kaylene J. Simpson 1 Victorian Centre for Functional Genomics, Peter MacCallum Cancer Centre; 2 Genome Informatics, The Kinghorn Cancer Centre, The Garvan Institute of Medical Research; 3 Metastasis Research Laboratory, Peter MacCallum Cancer Centre, 4 Sir Peter MacCallum Department of Oncology, University of Melbourne;

RNAi global collaboration study using Lincode siRNA in a primary screen of tumor and nontumor breast cell lines. Hundreds of lncRNAs are found to affect viability and cell morphology of breast cancer. Presented at Keystone Symposia on Long Noncoding RNAs: From Evolution to Function, Mar 15 - Mar 20, 2015.

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Specificity of highly potent miRNA inhibitors
Barbara Robertson, Andrew Dalby, Yuriy Fedorov, Jon Karpilow, Anastasia Khvorova1, Devin Leake, Annaleen Vermeulen

miRNA inhibitors are invaluable tools for elucidating the roles of miRNAs. However, potent inhibitors may also affect other miRNAs. To understand the potential cross-reactivity of miRNA inhibitors, various miRNA inhibitor designs were systematically tested. We demonstrate that mismatches both within and outside the seed region of the miRNA interfere with inhibition. Our findings indicate that features important for natural miRNA target recognition are also important for inhibitor specificity.

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Alternative miRNA design for therapeutic RNAi applications
Anja van Brabant Smith, Barb Robertson, Annaleen Vermeulen, Christina Yamada, Angela Reynolds, Anastasia Khvorova, Devin Leake

For in vivo applications, the design of miRNA inhibitors and miRNA mimics must be optimized for stability and potency. However, stabilized miRNA mimic molecules can lose functionality compared to standard miRNA mimic molecules due, in part, to the activity of the stabilized passenger strand acting as a miRNA inhibitor. We discuss how mismatches affect the activity of the stabilized miRNA mimics, perhaps by generating a passenger strand that is less functional as an inhibitor molecule.

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Cas9 driven by an optimal promoter improves gene editing in eukaryotic cell lines when paired with synthetic crRNA and tracrRNA
Amanda Haupt, Emily Anderson, Žaklina Strezoska, Hidevaldo Machado, Shawn McClelland, Maren Mayer, Adam Rocker, Annaleen Vermeulen, Amanda Birmingham, Melissa Kelley, Anja Smith

Presented here are results on the efficiency of using synthetic crRNA and tracrRNA to introduce gene editing events when co-transfected with a plasmid expressing Cas9. We explored the use of antibiotic and fluorescence activated cell sorting (FACS) methods for enrichment of cells that have undergone gene editing, and the use of multiple promoters to increase efficiency of gene editing with Cas9 and synthetic tracrRNA and crRNAs.

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Specificity and functionality of microRNA inhibitors
Barbara Robertson, Andrew Dalby, Jon Karpilow, Anastasia Khvorova, Devin Leake and Annaleen Vermeulen

Our findings indicate that features important for natural miRNA target recognition also appear to be important for inhibitor specificity. Understanding the specificity of inhibitors allows for better interpretation of inhibitor activity in endogenous systems.

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Identification of microRNA targets using microRNA modulation techniques and gene expression arrays
Emily M. Anderson, Maren Mayer, Kevin Sullivan, Barbara Robertson, Žaklina Strezoska, Annaleen Vermeulen, and Devin Leake

By examining the overlap of messages down-regulated by miRNA mimics and up-regulated by miRNA inhibitors, we robustly identify miRNA-regulated messages, many of which have canonical seed matches and some which are not identied by standard target prediction programs.

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siRNA Screening: Development of Hit Stratification Strategies
Žaklina Strezoska, Annaleen Vermeulen, Emily M. Anderson, Anja Smith, Devin Leake

This poster compares different approaches to hit stratification and validation after an initial screen. Standard siRNA reagents deconvoluted from a pooled set of four were compared to a pooled set of four specificity enhanced reagents. High confidence hits were similar. To explore the validity of low confidence hits, a chimeric approach was used whereby a gene-specific seed sequence was introduced into a non-targeting siRNA scaffold. This work resulted in new hit stratification strategies.

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The Chemical Synthesis of Long and Highly Modified RNA using 2'-ACE Chemistry
Xiaoqin Cheng, Kristina Larson, Letitia Kwok, David Mierzejewski, Shawn Begay, Randy Rauen, Kelly Grimsley, Kaizhang He, Michael Delaney, David Kitchen, Amanda Haas, Melissa Kelley, Anja van Brabant Smith

Dharmacon has previously developed a novel RNA synthesis chemistry making RNA synthesis as reliable, accessible and of comparable quality as routinely observed in DNA synthesis.

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Peanut Allergy: An epidemiologic analysis of a large database
Leickly, FE, Vitapur, G, and Kloepfer, K

Over three years, 700 children with a peanut story - either peanut sensitization or peanut allergy- were asked to participate in a database.

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Scientific News
Sorting Through Cellular Statistics
Aaron Dinner, professor in chemistry, and his graduate student Herman Gudjonson are trying to read the manual of life, DNA, as part of the Dinner group’s research into bioinformatics—the application of statistics to biological research.
Paving the way to Better Ovarian Cancer Diagnosis
Aïcha BenTaieb will present her invention for automated identification of ovarian cancer’s many subtypes at an international conference this fall.
New Tool Uses 'Drug Spillover' to Match Cancer Patients with Treatments
Researchers have developed a new tool that improves the ability to match drugs to disease: the Kinase Addiction Ranker (KAR) predicts what genetics are truly driving the cancer in any population of cells and chooses the best "kinase inhibitor" to silence these dangerous genetic causes of disease.
Computer Model Could Explain how Simple Molecules Took First Step Toward Life
Two Brookhaven researchers developed theoretical model to explain the origins of self-replicating molecules.
The Mystery of the Instant Noodle Chromosomes
Researchers from the Lomonosov Moscow State University evaluated the benefits of placing the DNA on the principle of spaghetti.
Web App Helps Researchers Explore Cancer Genetics
Brown University computer scientists have developed a new interactive tool to help researchers and clinicians explore the genetic underpinnings of cancer.
An Innovative Algorithm to Decipher How Drugs Work Inside the Body
Researchers at Columbia University Medical Center (CUMC) have developed a computer algorithm that is helping scientists see how drugs produce pharmacological effects inside the body.
How do Networks Shape the Spread of Disease and Gossip?
A team of mathematicians from Oxford University, University of North Carolina at Chapel Hill, and Rutgers University used a set of mathematical rules to encode how a contagion spreads, and then studied the outcomes of these rules.
AncestryDNA and Calico to Research the Genetics of Human Lifespan
Collaboration will analyze family history and genetics to facilitate development of cutting-edge therapeutics.
Informatics Tool Helps Scientists Prioritize Protein Modification Research
Researchers have developed a new informatics technology that analyzes existing data repositories of protein modifications and 3D protein structures to help scientists identify and target research on "hotspots" most likely to be important for biological function.
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