PPT-Clustering, Phylogenetic

Trees and Inferences about Evolution BMMB597E Protein Evolution 1 Given a set of organisms Can we measure similarities and cluster the organisms into subsets Can we form hierarchical clusterings. Losos Museum of Comparative Zoology and Department of Organismic and Evolutionary Biology Harvard University 26 Oxford Street Cambridge MA 02138 USA Correspondence Email jlososoebharvardedu Abstract Ecologists are increasingly adopting an evolutiona Central question in community ecology. What processes are responsible for the identity and relative abundances of co-occurring species in local assemblages?. What is the relative importance of different ecological processes in structuring communities. Lecture outline. Distance/Similarity between data objects. Data objects as geometric data points. Clustering problems and algorithms . K-means. K-median. K-center. What is clustering?. A . grouping. of data objects such that the objects . Haeckel’s evolutionary trees are among the first attempts at phylogeny inference.. Darwin’s tree. Schools of thought. A. Evolutionary Taxonomy. The basic view was that the best way to reconstruct the phylogeny of a group is to spend a lifetime learning everything one can about the biology of the group.. issue in . computing a representative simplicial complex. . Mapper does . not place any conditions on the clustering . algorithm. Thus . any domain-specific clustering algorithm can . be used.. We . Unsupervised . learning. Seeks to organize data . into . “reasonable” . groups. Often based . on some similarity (or distance) measure defined over data . elements. Quantitative characterization may include. Lecture outline. Distance/Similarity between data objects. Data objects as geometric data points. Clustering problems and algorithms . K-means. K-median. K-center. What is clustering?. A . grouping. of data objects such that the objects . Dr Laura Emery . Laura.Emery@ebi.ac.uk. www.ebi.ac.uk. Objectives. After this . tutorial you . should be able to. …. Discuss . the impact of a range of biological phenomena upon phylogenetic . inference. Log. 2. transformation. Row centering and normalization. Filtering. Log. 2. Transformation. Log. 2. -transformation makes sure that the noise is independent of the mean and similar differences have the same meaning along the dynamic range of the values.. 69 brought to you by CORE View metadata, citation and similar papers at core.ac.uk B. BRUVO-MAĐARIĆ: Molekularne �logenetske metode u entomologiji – nove spoznaje u evolucijskim odnosi Randomization tests. Cluster Validity . All clustering algorithms provided with a set of points output a clustering. How . to evaluate the “goodness” of the resulting clusters?. Tricky because . Takada N, Fujita H, Kawabata H, Takajo I, Sakata A, Takano A, et al. Spotted Fever Group Rickettsia sp. Closely Related to R. japonica, Thailand. Emerg Infect Dis. 2009;15(4):610-611. https://doi.org/10.3201/eid1504.071271. Tandy Warnow. Department of Computer Science. The Computational Historical Linguistics Project. http://. tandy.cs.illinois.edu. /. histling.html. Collaboration with Don . Ringe. began. in 1994; 17 papers since then, and two . Terminology. phylogeny . evolutionary history of a species or group of species. systematics. . classifying and determining evolutionary relationships of organisms . taxonomy . classifying and naming of organisms.