There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

A graph labeling is an assignment of integers to the vertices or edges, or both, subject to certain conditions. Graph labelings were first introduced in the late 1960s. In the intervening years dozens of graph labelings techniques have been studied in over 1000 papers. Finding out what has been done for any particular kind of labeling and keeping up with new discoveries is difficult because of the sheer number of papers and because many of the papers have appeared in journals that are not widely available. In this survey I have collected everything I could find on graph labeling. For the convenience of the reader the survey includes a detailed table of contents and index.

/pdf/a-dynamic-survey-of-graph-labeling-198znmwxtq.pdf

A Dynamic Survey of Graph Labeling

DNA sequencing with chain terminating inhibitors

The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons. REVEL was trained with recently discovered pathogenic and rare neutral missense variants, excluding those previously used to train its constituent tools. When applied to two independent test sets, REVEL had the best overall performance (p −12 ) as compared to any individual tool and seven ensemble methods: MetaSVM, MetaLR, KGGSeq, Condel, CADD, DANN, and Eigen. Importantly, REVEL also had the best performance for distinguishing pathogenic from rare neutral variants with allele frequencies

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Standards and Guidelines for the Interpretation and Reporting of Sequence Variants in Cancer: A Joint Consensus Recommendation of the Association for Molecular Pathology, American Society of Clinical Oncology, and College of American Pathologists

An interesting problem in musicology is to classify songs according to rhythms. A rhythm is represented by a sequence of "Quick" (Q) and "Slow" (S) symbols, which correspond to the (relative) duration of notes, such that S =2 Q. Recently, Christodoulakis et al. (16) presented an efficient algorithm that can be used to classify musical texts according to rhythms. In this paper, we implement the above algorithm along with the naive brute force algorithm to solve the same problem. We then analyze the theoretical time complexity bounds with the actual running times achieved by the experiments and compare the results of the two algorithms. Keywords— algorithms, music information retrieval, pat- tern matching, quick-slow, rhythm.

/pdf/implementation-of-algorithms-to-classify-musical-texts-2l5ethl65g.pdf

Implementation of Algorithms to Classify Musical Texts According to Rhythms

Bioinformatics Research and Development - Second International Conference, BIRD 2008 Vienna, Austria, July 7-9, 2008

This paper considers the construction of the suffix array of a string on the MasPar MP-2 architecture. suffix arrays are space-efficient variants of the suffix trees, a fundamental dictionary data structure that is the backbone of many string algorithms for pattern matching and textual information retreival. We adapt known PRAM techniques for implementation on the MasPar: bulletin boards, doubling techniques and sorting methods. Performance results are presented.

Massively Parallel Suffix Array Construction

Longest property-preserved common factor: A new string-processing framework

We study the λ-seed problem of a string in this paper. Given a string x of length n and an integer λ, the λ-seed problem is to find all the sets of λ substrings of x that cover a superstring of x, assuming that each element of the set is of equal length. We present an efficient algorithm that can compute all the λ-seeds of x in O(n2) time.

Costas S. Iliopoulos

Papers

Implementation of Algorithms to Classify Musical Texts According to Rhythms

Bioinformatics Research and Development - Second International Conference, BIRD 2008 Vienna, Austria, July 7-9, 2008

Massively Parallel Suffix Array Construction

Longest property-preserved common factor: A new string-processing framework

Computing the lambda -Seeds of a String.