SLIDER: Mining correlated motifs in protein-protein interaction networks

Abstract—Correlated motif mining (CMM) is the problem to find overrepresented pairs of patterns, called motif pairs, in interacting protein sequences. Algorithmic solutions for CMM thereby provide a computational method for predicting binding sites for protein interaction. In this paper, we adopt a motif-driven approach where the support of candidate motif pairs is evaluated in the network. We experimentally establish the superiority of the Chi-square-based support measure over other support measures. Furthermore, we obtain that CMM is an NP-hard problem for a large class of support measures (including Chi-square) and reformulate the search for correlated motifs as a combinatorial optimization problem. We then present the method SLIDER which uses local search with a neighborhood function based on sliding motifs and employs the Chi-square-based support measure. We show that SLIDER outperforms existing motif-driven CMM methods and scales to large protein-protein interaction networks

Implications of Weak-Interaction Space Deformation for Neutrino Mass Measurements

The negative values for the squares of both electron and muon neutrino masses obtained in recent experiments are explained as a possible consequence of a change in metric within the weak-interaction volume in the energy-momentum representation. Using a model inspired by a combination of the general theory of relativity and the theory of deformation for continuous media, it is shown that the negative value of the square of the neutrino mass can be obtained without violating allowed physical limits. The consequence is that the negative value is not necessary unphysical.Comment: 12 pages, 5 figures, LaTe

On Pebble Automata for Data Languages with Decidable Emptiness Problem

In this paper we study a subclass of pebble automata (PA) for data languages for which the emptiness problem is decidable. Namely, we introduce the so-called top view weak PA. Roughly speaking, top view weak PA are weak PA where the equality test is performed only between the data values seen by the two most recently placed pebbles. The emptiness problem for this model is decidable. We also show that it is robust: alternating, nondeterministic and deterministic top view weak PA have the same recognition power. Moreover, this model is strong enough to accept all data languages expressible in Linear Temporal Logic with the future-time operators, augmented with one register freeze quantifier.Comment: An extended abstract of this work has been published in the proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science (MFCS) 2009}, Springer, Lecture Notes in Computer Science 5734, pages 712-72

Hash function requirements for Schnorr signatures

We provide two necessary conditions on hash functions for the Schnorr signature scheme to be secure, assuming compact group representations such as those which occur in elliptic curve groups. We also show, via an argument in the generic group model, that these conditions are sufficient. Our hash function security requirements are variants of the standard notions of preimage and second preimage resistance. One of them is in fact equivalent to the Nostradamus attack by Kelsey and Kohno (Eurocrypt, Lecture Notes in Computer Science 4004: 183-200, 2006), and, when considering keyed compression functions, both are closely related to the ePre and eSec notions by Rogaway and Shrimpton (FSE, Lecture Notes in Computer Science 3017: 371-388, 2004). Our results have a number of interesting implications in practice. First, since security does not rely on the hash function being collision resistant, Schnorr signatures can still be securely instantiated with SHA-1/SHA-256, unlike DSA signatures. Second, we conjecture that our properties require O(2 n ) work to solve for a hash function with n-bit output, thereby allowing the use of shorter hashes and saving twenty-five percent in signature size. And third, our analysis does not reveal any significant difference in hardness between forging signatures and computing discrete logarithms, which plays down the importance of the loose reductions in existing random-oracle proofs, and seems to support the use of "normal-size” group

Measurement of urinary beta core fragment of human chorionic gonadotrophin in women with vulvovaginal malignancy and its prognostic significance

Tumours of the vulva and vagina are rare and there are relatively few studies of circulating markers in these conditions. The urinary measurement of the core fragment of the beta-subunit of hCG has been proposed as a useful tumour marker in non-trophoblastic gynaecological malignancies. This study describe the measurement of urinary beta-core in 50 patients with vulvovaginal malignancy. In contrast to other studies corrections were made for both the effect of urine concentration and the age of the patient. Each patient was followed up for at least 24 months, and at this time their status was correlated with their initial level of urinary beta-core. The sensitivity of beta-core was only 38%, but of those patients with elevated levels 90% had died within 24 months, while only 32% of those with normal levels had died. For both patients at initial presentation and those with recurrent disease, there was a highly significant difference in the survival curve between those with elevated beta-core levels and those with normal levels. This is similar to findings in cervical carcinoma, and suggests that for lower genital tract cancer the measurement of urinary beta-core may be valuable as a prognostic indicator, allowing a more informed approach to treatment and follow-up

Streaming Tree Transducers

Theory of tree transducers provides a foundation for understanding expressiveness and complexity of analysis problems for specification languages for transforming hierarchically structured data such as XML documents. We introduce streaming tree transducers as an analyzable, executable, and expressive model for transforming unranked ordered trees in a single pass. Given a linear encoding of the input tree, the transducer makes a single left-to-right pass through the input, and computes the output in linear time using a finite-state control, a visibly pushdown stack, and a finite number of variables that store output chunks that can be combined using the operations of string-concatenation and tree-insertion. We prove that the expressiveness of the model coincides with transductions definable using monadic second-order logic (MSO). Existing models of tree transducers either cannot implement all MSO-definable transformations, or require regular look ahead that prohibits single-pass implementation. We show a variety of analysis problems such as type-checking and checking functional equivalence are solvable for our model.Comment: 40 page