Learning DNA mutational signatures using neural networks

Kõik pahaloomulised vähkkasvajad on põhjustatud organismi rakkudes\n\rtoimuvate mutatsioonide poolt. On leitud, et need mutatsioonid\n\ron moodustatud spetsiifiliste mustrite ehk signatuuride kombinatsioonist,\n\rmille aluseks olevad protsessid on tihti teada. Seetõttu on nende\n\rsignatuuride õppimine andmetest väga tähtis — see võib anda paremat\n\rinformatsiooni vähkkasvajate mehhanismide kohta ja olla abiks\n\rvähi ennetamisel ja teraapial. Antud töö eesmärk on testida ja võrrelda\n\rerinevaid metoodikaid, et parandada mutatsiooniliste signatuuride\n\rleidmist. Me võrdlesime kolme uut meetodit — tehis-närvivõrgud\n\r(NN), mittenegatiivsed faktorvõrgud (RFN) ja teemade modelleerimine\n\r— praegu kasutatava mittenegatiivse maatriksi faktoriseerimisega\n\r(NMF). Me eksperimenteerisime meetoditega kolmel orgaanilisel ja kolmel\n\rsünteetilisel andmestikul ning mõõtsime rekonstrueerimise viga, tulemuse\n\rhõredust ja arvutusteks kulunud aega. Tulemused näitavad, et\n\rNMF annab väikseima veaga tulemuse kergematel andmestikel, kuid ka\n\rRFN-i tulemus on ligilähedane ning kõikidel teistel andmestikel saavutab\n\rsee parema tulemuse. NN esineb sama hästi kui RFN keerulisematel\n\randmestikel ning lisaks saavutab üleüldiselt kõige hõredamad tulemused.\n\rNMF-i eeliseks on stabiilsuse arvutamise funktsionaalsus, mis väga\n\rtäpselt suudab määrata õige signatuuride arvu. Tulevikus tuleb teha\n\redasist arendustööd, et sarnane võimekus ka RFN ja NN meetoditele\n\rlisada, mille järel oleks võimalik nende praktiline kasutamine mutatsiooniliste\n\rsignatuuride õppimisel.All cancers are caused by mutations in the cells of an organism. It\n\ris found that these mutations result from the combination of specific\n\rmutational signatures, which often have known underlying processes.\n\rThat is why learning these signatures is important — it can give better\n\rinformation about the mechanisms of cancers and also be helpful for\n\rcancer prevention and therapy. The aim of this thesis is to test and\n\rcompare different methodology to improve the discovery of mutational\n\rsignatures. In particular, we compared three new methods of neural\n\rnetworks (NN), rectified factor networks (RFN) and topic modelling\n\rto the currently used non-negative matrix factorization (NMF). We\n\rexperimented with the methods on three organic and three synthetic\n\rdata sets by measuring reconstruction error, sparsity and time taken\n\rand compared them with NMF. The results show that NMF produces\n\rthe smallest error on easier data sets, but error of RFN is comparably\n\rgood also and on all other data sets produces the best result. NN\n\rperforms equally well with RFN on more difficult data sets and overall\n\rproduces the sparsest results. The advantage of NMF is the stability\n\rfunctionality that determines very well the correct number of signatures.\n\rFuture work will be needed to add this capability to RFN and\n\rNN methods which would enable their practical use for the problem of\n\rfinding mutational signatures

Hilise põlveliigese osteoartroosiga patsientide alajäsemete liigeste dünaamiliste näitjate muutused kõnnil enne ja pärast 8-nädalast koduse kehalise harjutuste programmi sooritamist

http://www.ester.ee/record=b444224

Estonian football specific corpora automatic semantic role labeling with football specific Framenet

Käesoleva töö eesmärgiks on uurida ning üritada lahendada eestikeelse teksti automaatse freimidega märgendamise probleemi. Üldine eestikeelne Framenet on alles algusjärgus, kuid olemas on terviklik jalgpalli-alane freimide ressurss, mille abil üritame tõestada hüpoteesi, et jalgpalli-alase teksti märgendamiseks piisab vaid morfoloogilisest ning süntaktilisest infost. Sellele hüpoteesile me siiski kinnitust ei saanud, kuna sama tähendust kandvat lauset on võimalik esitada liiga paljudel erinevatel viisidel. Lisaks täiendasime jalgpalli-alaste sõnadega Eesti suurimat leksikaal-semantilist andmebaasi, Wordnetti.Research and a possible solution to the problem of automatic semantic role labeling of text in Estonian is carried out in this paper. A general Estonian Framenet is in the starting phase, but there is also available a football specific Framenet. We try to prove the hypothesis that morphological and syntactical information is enough for automatic semantic role labeling in football related corpora. Unfortunately, we did not achieve a confirmation for the hypothesis, because there are too many ways to present sentences that have the same meaning. In addition, we supplemented Estonian biggest lexical-syntactic database with football related words

Shape-Dependent Electrocatalysis: Oxygen Reduction on Carbon-Supported Gold Nanoparticles

Cubic, octahedral and quasi-spherical (two different particle sizes) Au nanoparticles are synthesised and dispersed in a carbon-black powder. The size and morphology of the Au nanocatalysts is confirmed by transmission electron microscopy and X-ray diffraction. Au nanospheres are approximately 5 and 30 nm in diameter, whereas the size of Au octahedra and nanocubes is approximately 40–45 nm. The electrocatalytic activity of these carbon-supported particles towards the oxygen reduction reaction (ORR) is studied in 0.5 M H2SO4 and 0.1 M KOH solutions by using the rotating-disk-electrode method. The specific activity (SA) for O2 reduction is measured, and the highest SA is observed for Au nanocubes supported on carbon. The highest mass activities are found for the smallest Au nanoparticles. Tafel analysis suggests that the mechanism of the ORR on shape-controlled Au/C catalysts is the same as on bulk Au.This research was financially supported by institutional research funding (IUT 20–16) of the Estonian Ministry of Education and Research and by the Estonian Research Council (Grant No. 8380), by Archimedes Foundation (Project No. 3.2.0501.10–0015), by the MCINN-FEDER (Spain) (project CTQ 2010–16271) and by the Generalitat Valenciana (project PROMETEO/2009/045)

PdPt alloy nanocubes as electrocatalysts for oxygen reduction reaction in acid media

In this work, PdPt alloy nanocubes with different metal ratios were synthesised in the presence of polyvinylpyrrolidone (PVP). The surface morphology of the PdPt samples was characterised by transmission electron microscopy (TEM). TEM images showed that PdPt nanoparticles were cubic-shaped and the average size of the cubes was about 8–10 nm. Their electrocatalytic activity towards the oxygen reduction reaction (ORR) was studied in 0.5 M H2SO4 using the rotating disc electrode method. All the alloyed catalysts showed enhanced electrocatalytic activity for ORR as compared to the monometallic cubic Pd nanoparticles. Half-wave potential values for PdPt catalysts were comparable with that of Pt nanocubes. From the alloyed catalysts Pd36Pt64 exhibited the highest specific activity, which was only slightly lower than that of cubic Pt nanoparticles. The Koutecky–Levich analysis revealed that the reduction of oxygen proceeded via 4-electron pathway on all the electrocatalysts studied.This research was financially supported by institutional research funding (IUT20-16) of the Estonian Ministry of Education and Research and by the Estonian Research Council (Grant No. 9323) and by Archimedes Foundation (Project No. 3.2.0501.10-0015). KJ thanks the Archimedes Foundation for scholarship. JMF acknowledges financial support from MINECO (Spain), project CTQ2013-44083-P

Recent progress in oxygen reduction electrocatalysis on Pd-based catalysts

Palladium-based catalysts for electrochemical reduction of oxygen have received increasing attention as potential replacement for platinum-based materials in the fuel cells. This Review summarises the research conducted with nanostructured palladium catalysts, including thin nanostructured films and Pd nanoparticles on various carbon and non-carbon supports. The mechanism of oxygen reduction on palladium is described and the effect of the particle size and shape on the electrocatalytic activity is emphasised. The role of the support material and additives on the oxygen reduction activity of Pd nanoparticles is also discussed. The electrocatalytic activity of Pd-based catalysts is evaluated in terms of specific activity and mass activity. The application of supported Pd nanoparticles as cathode catalysts for low-temperature fuel cells is highlighted. Some insights into the remaining challenges and directions for further development of Pd-based oxygen reduction electrocatalysts are provided.This work was financially supported by institutional research funding (IUT20-16) of the Estonian Ministry of Education and Research. We would like to acknowledge the financial support by the EU through the European Regional Development Fund (TK141 “Advanced materials and high-technology devices for energy recuperation systems”)

Oxygen electroreduction on carbon-supported Pd nanocubes in acid solutions

The oxygen reduction reaction (ORR) was studied on carbon-supported cubic palladium nanoparticles of different sizes (∼30 nm, ∼10 nm and ∼7 nm). Cetyltrimethylammonium bromide (CTAB) and polyvinylpyrrolidone (PVP) were used as capping agents to prepare the nanocubes and Pd content in the catalyst samples was 20 and 50 wt%. The surface morphology of the prepared materials was studied by transmission electron microscopy (TEM). The catalyst materials were electrochemically characterised by cyclic voltammetry and CO stripping experiments. The rotating disk electrode (RDE) method was employed for ORR studies in 0.5 M H2SO4 and 0.1 M HClO4 solutions. The ORR results revealed that the specific activity of cubic Pd nanoparticles is higher than that of spherical Pd particles and does not depend on the Pd content in the catalyst, but decreases with decreasing the size of Pd nanocubes. Mass activity of Pd nanocubes increased with decreasing the particle size. The ORR proceeds mainly via 4-electron pathway and the reaction mechanism is similar to that on bulk Pd.This research was financially supported by institutional research funding (IUT20-16) of the Estonian Ministry of Education and Research and by the Estonian Research Council (Grant No. 9323). HE thanks the Archimedes Foundation for scholarship. JMF acknowledges financial support from MINECO (Spain), project CTQ2013-44083-P

Oxygen reduction reaction on carbon-supported palladium nanocubes in alkaline media

Carbon-supported Pd nanocubes with the size of 30, 10 and 7 nm were prepared and their electrocatalytic activity towards the oxygen reduction reaction (ORR) in alkaline solution was studied. For comparison carbon-supported spherical Pd nanoparticles and commercial Pd/C catalyst were used. The catalysts were characterised by transmission electron microscopy, electro-oxidation of carbon monoxide and cyclic voltammetry and the ORR activity was evaluated using the rotating disk electrode method. The ORR on all studied Pd/C catalysts proceeded via four-electron pathway where the rate-limiting step was the transfer of the first electron to O2 molecule. The specific activity of Pd nanocubes was more than two times higher than that of spherical Pd nanoparticles and increased with increasing the particle size.This research was financially supported by institutional research funding (IUT20-16) by the Estonian Ministry of Education and Research and by the Estonian Research Council (Grant No. 9323)

Biomass-derived activated carbon as high-performance non-precious electrocatalyst for oxygen reduction

A new type of Fe and N doped carbon material is synthesized by pyrolyzing ferric chloride doped egg white (EW) and the proposed synthetic route is easy, green, and low-cost. In addition, the as-prepared sample exhibits a feasible magnetism and comparable oxygen reduction reaction (ORR) activity to commercial Pt/C.Web of Scienc