PPT-piRNA Detection Via Multidimensional Small RNA Clustering

Author : welnews | Published Date : 2020-08-29

Presented by Stephanie Schustermann Supervisors Prof Eitan Bachmat Dr Alal Eran Mr Amitai Mordechai Faculty of Natural Sciences The Department of Computer Science

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piRNA Detection Via Multidimensional Small RNA Clustering: Transcript

Presented by Stephanie Schustermann Supervisors Prof Eitan Bachmat Dr Alal Eran Mr Amitai Mordechai Faculty of Natural Sciences The Department of Computer Science BenGurion University of the Negev. Adapted from Chapter 3. Of. Lei Tang and . Huan. Liu’s . Book. Slides prepared by . Qiang. Yang, . UST, . HongKong. 1. Chapter 3, Community Detection and Mining in Social Media. Lei Tang and Huan Liu, Morgan & Claypool, September, 2010. . -. Traffic Video Surveillance. Ziming. Zhang, . Yucheng. Zhao and . Yiwen. Wan. Outline. Introduction. &Motivation. Problem Statement. Paper Summeries. Discussion and Conclusions. What are . Anomalies?. Spectral. . Estimates. for . Engineering. . P. roblems. : . Case-. study. Aimé Lay-Ekuakille. University. of Salento. . Index:. Problem. statement. Main. . motivation. FDM-. Filter. . D. iagonalization. Wei Wang. Department of Computer Science. Scalable Analytics Institute. UCLA. weiwang@cs.ucla.edu. Graphs/Networks. FFSM (ICDM03), SPIN (KDD04),. GDIndex. (ICDE07). MotifMining. (PSB04, RECOMB04, ProteinScience06, SSDBM07, BIBM08). input data are ranks: most similar pair AB. <. CB. <. AC most different pair, or input data are rating scales: (very similar 1. . .9 very different), but we don't believe in assuming interval level property of data.. Vaibhav. . Mallya. EECS 767. D. . Radev. 1. Agenda. Agenda. Basic Definitions. Girvan-Newman Algorithm. Donetti. -Munoz Spectral Method. Karypis. -Kumar Multi-level Partitioning. Graclus. GraphClust. 2. /86. Contents. Statistical . methods. parametric. non-parametric (clustering). Systems with learning. 3. /86. Anomaly detection. Establishes . profiles of normal . user/network behaviour . Compares . Lecture . 6. Dr. Lev . Faivishevsky. March, 2016. Agenda. Clustering. Hierarchical. K-means. GMM. Anomaly Detection. Change Detection. 3. Clustering. Partition unlabeled examples into disjoint subsets of . academy.zariba.com. 1. Lecture Content. Matrices and Multidimensional Arrays. The . Array. Class. Structs and Array.Sort. 2. Multidimensional Arrays. 3. . An . array. is . multidimensional. if it has more than one . microRNA. . siRNA. . piwiRNA. 2. Homework (part. 1, watching . assignment). . www.massachusetts.edu/mello/index.html. https://www.youtube.com/watch?v=. 5ZE7o_bRekk. (Video for HW#1). Write . down all important and interesting facts on . Fig1piRNAbiosynthesismechanismWithinthenucleustwotypesofpiRNAclustersaretranscribedtoproducetheprimarypiRNAsZucanditsco-factorsincisedprimarypiRNAsproducingpiRNAintermediateswitha52uracilinYbbodypiRNA and the usage of them in antiviral immunity . Heleri Kirsip. Bioinformaatika. JC. 10.11.2016. Mis. on . endogeenne. . viiruslik. element (EVE)?. Endogeensed viiruslikud elemendid – viiruse g. enoom. 14. . World-Leading Research with Real-World Impact!. CS 5323. Outline. Anomaly detection. Facts and figures. Application. Challenges. Classification. Anomaly in Wireless. . 2. Recent News. Hacking of Government Computers Exposed 21.5 Million People. Winkenbach. Nishimura Lab. 2. 3. Paragraphs. A uniform paragraph relates the content to the declared topic sentence. Adopting a standard of organization in your paragraphs adds fluency. General to specific.

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