Towards a Definitive Measure of Repetitiveness

Unlike in statistical compression, where Shannon’s entropy is a definitive lower bound, no such clear measure exists for the compressibility of repetitive sequences. Since statistical entropy does not capture repetitiveness, ad-hoc measures like the size z of the Lempel–Ziv parse are frequently used to estimate repetitiveness. Recently, a more principled measure, the size γ of the smallest string attractor, was introduced. The measure γ lower bounds all the previous relevant ones (including z), yet length-n strings can be represented and efficiently indexed within space O(γlognγ), which also upper bounds most measures (including z). While γ is certainly a better measure of repetitiveness than z, it is NP-complete to compute, and no o(γlog n) -space representation of strings is known. In this paper, we study a smaller measure, δ≤ γ, which can be computed in linear time. We show that δ better captures the compressibility of repetitive strings. For every length n and every value δ≥ 2, we construct a string such that γ=Ω(δlognδ). Still, we show a representation of any string S in O(δlognδ) space that supports direct access to any character S[i] in time O(lognδ) and finds the occ occurrences of any pattern P[1.m] in time O(mlog n+ occlogεn) for any constant ε> 0. Further, we prove that no o(δlog n) -space representation exists: for every length n and every value 2 ≤ δ≤ n1-ε, we exhibit a string family whose elements can only be encoded in Ω(δlognδ) space. We complete our characterization of δ by showing that, although γ, z, and other repetitiveness measures are always O(δlognδ), for strings of any length n, the smallest context-free grammar can be of size Ω(δlog2n/ log log n). No such separation is known for γ

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1.

In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field

Pattern matching in strings

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