Sparse Positional Strategies for Safety Games

We consider the problem of obtaining sparse positional strategies for safety games. Such games are a commonly used model in many formal methods, as they make the interaction of a system with its environment explicit. Often, a winning strategy for one of the players is used as a certificate or as an artefact for further processing in the application. Small such certificates, i.e., strategies that can be written down very compactly, are typically preferred. For safety games, we only need to consider positional strategies. These map game positions of a player onto a move that is to be taken by the player whenever the play enters that position. For representing positional strategies compactly, a common goal is to minimize the number of positions for which a winning player's move needs to be defined such that the game is still won by the same player, without visiting a position with an undefined next move. We call winning strategies in which the next move is defined for few of the player's positions sparse. Unfortunately, even roughly approximating the density of the sparsest strategy for a safety game has been shown to be NP-hard. Thus, to obtain sparse strategies in practice, one either has to apply some heuristics, or use some exhaustive search technique, like ILP (integer linear programming) solving. In this paper, we perform a comparative study of currently available methods to obtain sparse winning strategies for the safety player in safety games. We consider techniques from common knowledge, such as using ILP or SAT (satisfiability) solving, and a novel technique based on iterative linear programming. The results of this paper tell us if current techniques are already scalable enough for practical use.Comment: In Proceedings SYNT 2012, arXiv:1207.055

Driver Gene and Novel Mutations in Asbestos-Exposed Lung Adenocarcinoma and Malignant Mesothelioma Detected by Exome Sequencing

Background Asbestos is a carcinogen linked to malignant mesothelioma (MM) and lung cancer. Some gene aberrations related to asbestos exposure are recognized, but many associated mutations remain obscure. We performed exome sequencing to determine the association of previously known mutations (driver gene mutations) with asbestos and to identify novel mutations related to asbestos exposure in lung adenocarcinoma (LAC) and MM. MethodsExome sequencing was performed on DNA from 47 tumor tissues of MM (21) and LAC (26) patients, 27 of whom had been asbestos-exposed (18 MM, 9 LAC). In addition, 9 normal lung/blood samples of LAC were sequenced. Novel mutations identified from exome data were validated by amplicon-based deep sequencing. Driver gene mutations in BRAF, EGFR, ERBB2, HRAS, KRAS, MET, NRAS, PIK3CA, STK11, and ephrin receptor genes (EPHA1-8, 10 and EPHB1-4, 6) were studied for both LAC and MM, and in BAP1, CUL1, CDKN2A, and NF2 for MM. ResultsIn asbestos-exposed MM patients, previously non-described NF2 frameshift mutation (one) and BAP1 mutations (four) were detected. Exome data mining revealed some genes potentially associated with asbestos exposure, such as MRPL1 and SDK1. BAP1 and COPG1 mutations were seen exclusively in MM. Pathogenic KRAS mutations were common in LAC patients (42 %), both in non-exposed (n = 5) and exposed patients (n = 6). Pathogenic BRAF mutations were found in two LACs. ConclusionBAP1 mutations occurred in asbestos-exposed MM. MRPL1, SDK1, SEMA5B, and INPP4A could possibly serve as candidate genes for alterations associated with asbestos exposure. KRAS mutations in LAC were not associated with asbestos exposure.Peer reviewe

Targeted Resequencing Reveals ALK Fusions in Non-Small Cell Lung Carcinomas Detected by FISH, Immunohistochemistry, and Real-Time RT-PCR: A Comparison of Four Methods

Peer reviewe

Mooren koneiden syntetisointi LTL-määrittelyistä

Moore machine is a finite state machine with output and it is a common model for digital circuits. The LTL synthesis problem is to decide whether there exists a Moore machine which satisfies a given specification expressed in the Linear Temporal Logic (LTL), and if so, give such a machine. If we could synthesize Moore machines automatically from their specification, the developer would he freed from manually writing the implementation. Automated synthesis also allows one to analyze the consistency and completeness of specifications, which currently seems a more realistic aim than to completely replace manual programming. A synthesis algorithm detects if a specification is not realizable, and unintended behaviour of a synthesized program may lead one to discover under specification issues. However, the high computational complexity of the problem in the general case has discouraged researchers and little of the theory developed during the past decades has been put into practice. This Thesis presents three approaches to the synthesis problem: The first one is a classic, based on deterministic omega-automata. The second one reduces the problem to determining winning strategies in a safety game, where the synthesizer loses if the environment giving inputs violates the specification. The third one is a reduction to an instance of Difference Logic which is certifiable if and only if there exists a program of size at most a predefined bound. All three have been implemented and experimental data is provided on their applicability to some benchmarks. The main result is that the safety game approach can be considered relatively efficient and viable also for non-trivial specifications, whereas the other two do not scale up on our benchmarks. On the other hand, the Difference Logic approach has to its considerable advantage that it produces minimal Moore machines which implement the specification.Mooren kone on äärellinen tilakone. jolla on ulostuloja. Niitä käytetään yleisesti mallintamaan digitaalisia piirejä. LTL-synteesiongelma on ratkaista, onko olemassa Mooren konetta, joka toteuttaisi annetun lineaarisen aikalogiikalla (LTL) ilmaistun määrittelyn. Mikäli on, annetaan toteuttava Mooren kone vastauksena. Jos tilakoneet voitaisiin syntetisoida määrittelystä automaattisesti, vapautuisi kehittäjä kirjoittamasta toteutusta käsin. Syntetisointi mahdollistaa myös määrittelyjen ristiriidattomuuden ja kattavuuden analysoinnin. mikä vaikuttaa tällä hetkellä realistisemmalta tavoitteelta kuin ohjelmoinnin täydellinen automatisointi. Synteesialgoritmi huomaa. mikäli määrittely on sisäisesti ristiriitainen eikä siis ole ollenkaan toteutettavissa. ja toisaalta syntetisoidun tilakoneen odottamaton käytös voi auttaa löytämään määrittelyn puutteita. Synteesiongelman laskennallinen vaativuus todettiin kuitenkin yleisessä tapauksessa hyvin korkeaksi, mikä ei ole kannustanut tutkijoita uhraamaan merkittäviä resursseja varsinkaan käytännön ratkaisujen etsimiseen, vaikka teoria onkin vuosikymmenten kuluessa kehittynyt. Tämä diplomityö esittelee kolme lähestymistapaa synteesiongelmaan: Ensimmäinen on klassisin, ja perustuu omega-tilakoneiden determinisointiin. Toinen palauttaa ongelman voittostrategian etsimiseen turvapelissä. jossa syntetisoija häviää, mikäli syötteen antava ympäristö rikkoo määrittelyä. Kolmas menetelmä palauttaa ongelman differenssilogiikan instanssiksi. joka on toteutuva jos ja vain jos on olemassa korkeintaan annetun vakion kokoinen Mooren kone, joka toteuttaa määrittelyn. Kaikki kolme menetelmää on toteutettu ja koeteltu muutamilla määrittelyillä. Tärkein tutkimustulos on. että vain turvapeliin perustuva menetelmä pystyy ratkaisemaan ongelman ei-triviaaleille määrittelyille. Kaksi muuta lähestymistapaa eivät löydä ratkaisua tämän työn määrittelyille ajan ja muistin mielekkäissä rajoissa. Toisaalta differenssilogiikkamenetelmän merkittävä etu on. että sillä voi löytää pienimmän mahdollisen ratkaisun

Targeted Resequencing of 9p in Acute Lymphoblastic Leukemia Yields Concordant Results with Array CGH and Reveals Novel Genomic Alterations

Genetic alterations of the short arm of chromosome 9 are frequent in acute lymphoblastic leukemia. We performed targeted sequencing of 9p region in 35 adolescent and adult acute lymphoblastic leukemia patients and sought to investigate the sensitivity of detecting copy number alterations in comparison with array comparative genomic hybridization (aCGH), and besides, to detect novel genetic anomalies. We found a high concordance of copy number variations (CNVs) as detected by next generation sequencing (NGS) and aCGH. By both methodologies, the recurrent deletion at CDKN2A/B locus was identified, whereas NGS revealed additional, small regions of CNVs, seen more frequently in adult patients, while aCGH was better at detecting larger CNVs. Also, by NGS, we detected novel structural variations, novel SNVs and small insertion/deletion variants. Our results show that NGS, in addition to detecting mutations and other genetic aberrations, can be used to study CNV