OTU deubiquitinases reveal mechanisms of linkage specificity and enable ubiquitin chain restriction analysis

Sixteen ovarian tumor (OTU) family deubiquitinases (DUBs) exist in humans, and most members regulate cell-signaling cascades. Several OTU DUBs were reported to be ubiquitin (Ub) chain linkage specific, but comprehensive analyses are missing, and the underlying mechanisms of linkage specificity are unclear. Using Ub chains of all eight linkage types, we reveal that most human OTU enzymes are linkage specific, preferring one, two, or a defined subset of linkage types, including unstudied atypical Ub chains. Biochemical analysis and five crystal structures of OTU DUBs with or without Ub substrates reveal four mechanisms of linkage specificity. Additional Ub-binding domains, the ubiquitinated sequence in the substrate, and defined S1’ and S2 Ub-binding sites on the OTU domain enable OTU DUBs to distinguish linkage types. We introduce Ub chain restriction analysis, in which OTU DUBs are used as restriction enzymes to reveal linkage type and the relative abundance of Ub chains on substrates

LINKAGE AND DUALITY OF MODULES

Martsinkovsky and Strooker [13] recently introduced module theoretic linkage using syzygy and transpose. This generalization brings possibility of much application of linkage, especially, to homological theory of modules. In the present paper, we connect linkage of modules to certain duality of modules. We deal with Gorenstein dimension, Cohen-Macaulay modules over a Gorenstein local ring using linkage and generalize the results to non-commutative algebras.</p

Data linkage algebra, data linkage dynamics, and priority rewriting

We introduce an algebra of data linkages. Data linkages are intended for modelling the states of computations in which dynamic data structures are involved. We present a simple model of computation in which states of computations are modelled as data linkages and state changes take place by means of certain actions. We describe the state changes and replies that result from performing those actions by means of a term rewriting system with rule priorities. The model in question is an upgrade of molecular dynamics. The upgrading is mainly concerned with the features to deal with values and the features to reclaim garbage.Comment: 48 pages, typos corrected, phrasing improved, definition of services replaced; presentation improved; presentation improved and appendix adde

Improving the evaluation of web search systems

Linkage analysis as an aid to web search has been assumed to be of significant benefit and we know that it is being implemented by many major Search Engines. Why then have few TREC participants been able to scientifically prove the benefits of linkage analysis over the past three years? In this paper we put forward reasons why disappointing results have been found and we identify the linkage density requirements of a dataset to faithfully support experiments into linkage analysis. We also report a series of linkage-based retrieval experiments on a more densely linked dataset culled from the TREC web documents

Generalized Bayesian Record Linkage and Regression with Exact Error Propagation

Record linkage (de-duplication or entity resolution) is the process of merging noisy databases to remove duplicate entities. While record linkage removes duplicate entities from such databases, the downstream task is any inferential, predictive, or post-linkage task on the linked data. One goal of the downstream task is obtaining a larger reference data set, allowing one to perform more accurate statistical analyses. In addition, there is inherent record linkage uncertainty passed to the downstream task. Motivated by the above, we propose a generalized Bayesian record linkage method and consider multiple regression analysis as the downstream task. Records are linked via a random partition model, which allows for a wide class to be considered. In addition, we jointly model the record linkage and downstream task, which allows one to account for the record linkage uncertainty exactly. Moreover, one is able to generate a feedback propagation mechanism of the information from the proposed Bayesian record linkage model into the downstream task. This feedback effect is essential to eliminate potential biases that can jeopardize resulting downstream task. We apply our methodology to multiple linear regression, and illustrate empirically that the "feedback effect" is able to improve the performance of record linkage.Comment: 18 pages, 5 figure

Robust Group Linkage

We study the problem of group linkage: linking records that refer to entities in the same group. Applications for group linkage include finding businesses in the same chain, finding conference attendees from the same affiliation, finding players from the same team, etc. Group linkage faces challenges not present for traditional record linkage. First, although different members in the same group can share some similar global values of an attribute, they represent different entities so can also have distinct local values for the same or different attributes, requiring a high tolerance for value diversity. Second, groups can be huge (with tens of thousands of records), requiring high scalability even after using good blocking strategies. We present a two-stage algorithm: the first stage identifies cores containing records that are very likely to belong to the same group, while being robust to possible erroneous values; the second stage collects strong evidence from the cores and leverages it for merging more records into the same group, while being tolerant to differences in local values of an attribute. Experimental results show the high effectiveness and efficiency of our algorithm on various real-world data sets