Algorithms in bioinformatics

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This work covers a range of topics in computational biology, focusing on algorithms and methodologies for analyzing gene expression, phylogeny, networks, genome rearrangements, sequences, and structure. It discusses spectral clustering for grouping genes based on function and presents dynamic de-novo prediction of microRNAs influenced by cell conditions. The text introduces a linear time biclustering algorithm for time series gene expression data and examines developmental gene expression analysis across multiple genetic backgrounds. In phylogeny, it explores algorithms for maximum quartet consistency and quartet distances, enhancing supertree resolvability through semi-definite programming. The work addresses haplotyping problems using hidden Markov techniques and algorithms for imperfect phylogeny haplotyping. Network analysis is tackled with faster algorithms for detecting motifs and reconstructing metabolic networks. Genome rearrangements are discussed through approximation algorithms for sorting by transpositions and new bounds on transposition distances. For sequences, a unifying framework for seed sensitivity is proposed, alongside methods for aligning tandem repeats and RNA structures. It also presents advancements in protein threading, biopolymer structure-sequence alignment, and the discovery of protein substructures in electron microscopy maps. Overall, the content emphasizes innovative computational technique