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.

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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

We present a generalization of a known fact from combinatorics on words related to periodicity into quasiperiodicity. A string is called periodic if it has a period which is at most half of its length. A string $w$ is called quasiperiodic if it has a non-trivial cover, that is, there exists a string $c$ that is shorter than $w$ and such that every position in $w$ is inside one of the occurrences of $c$ in $w$. It is a folklore fact that two strings that differ at exactly one position cannot be both periodic. Here we prove a more general fact that two strings that differ at exactly one position cannot be both quasiperiodic. Along the way we obtain new insights into combinatorics of quasiperiodicities.

Two strings at Hamming distance 1 cannot be both quasiperiodic

This paper provides an overview of six particular problems of palindromic factorization and recent algorithmic improvements in solving them.

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Recent Advances of Palindromic Factorization.

/pdf/spambots-creative-deception-4jbrqm8x1g.pdf

Spambots: Creative Deception

A Structured Motif refers to a sequence of simple motifs with distance constraints. We present SimpLiSMS, a simple, lightweight and fast algorithm for searching structured motifs. SimpLiSMS does not use any sophisticated data structure, which makes it simple and lightweight. Our experiments show excellent performance of SimpLiSMS. Furthermore, we introduce a parallel version of SimpLiSMS which runs even faster.

SimpLiSMS: A Simple, Lightweight and Fast Approach for Structured Motifs Searching

A weighted biological sequence is a string in which a set of characters may appear at each position with respective probabilities of occurrence. We attempt to locate all the tandem repeats in a weighted sequence. By introducing the idea of equivalence classes in weighted sequences, we identify the tandem repeats of every possible length using an iterative partitioning technique, and present the O(n 2) time algorithm.

Costas S. Iliopoulos

Papers

Two strings at Hamming distance 1 cannot be both quasiperiodic

Recent Advances of Palindromic Factorization.

Spambots: Creative Deception

SimpLiSMS: A Simple, Lightweight and Fast Approach for Structured Motifs Searching

Locating Tandem Repeats in Weighted Biological Sequences