Comorbidities in the diseasome are more apparent than real: What Bayesian filtering reveals about the comorbidities of depression

Comorbidity patterns have become a major source of information to explore shared mechanisms of pathogenesis between disorders. In hypothesis-free exploration of comorbid conditions, disease-disease networks are usually identified by pairwise methods. However, interpretation of the results is hindered by several confounders. In particular a very large number of pairwise associations can arise indirectly through other comorbidity associations and they increase exponentially with the increasing breadth of the investigated diseases. To investigate and filter this effect, we computed and compared pairwise approaches with a systems-based method, which constructs a sparse Bayesian direct multimorbidity map (BDMM) by systematically eliminating disease-mediated comorbidity relations. Additionally, focusing on depression-related parts of the BDMM, we evaluated correspondence with results from logistic regression, text-mining and molecular-level measures for comorbidities such as genetic overlap and the interactome-based association score. We used a subset of the UK Biobank Resource, a cross-sectional dataset including 247 diseases and 117,392 participants who filled out a detailed questionnaire about mental health. The sparse comorbidity map confirmed that depressed patients frequently suffer from both psychiatric and somatic comorbid disorders. Notably, anxiety and obesity show strong and direct relationships with depression. The BDMM identified further directly co-morbid somatic disorders, e.g. irritable bowel syndrome, fibromyalgia, or migraine. Using the subnetwork of depression and metabolic disorders for functional analysis, the interactome-based system-level score showed the best agreement with the sparse disease network. This indicates that these epidemiologically strong disease-disease relations have improved correspondence with expected molecular-level mechanisms. The substantially fewer number of comorbidity relations in the BDMM compared to pairwise methods implies that biologically meaningful comorbid relations may be less frequent than earlier pairwise methods suggested. The computed interactive comprehensive multimorbidity views over the diseasome are available on the web at Co=MorNet: bioinformatics.mit.bme.hu/UKBNetworks

Kombinatorikus optimalizálás alkalmazásai a villamosságtanban = Combinatorial optimization and its applications in electrical engineering

A kombinatorikus optimalizálás eszközeit (gráf- és matroidelméleti algoritmusok, bonyolultságelméleti vizsgálatok) alkalmaztuk villamosságtani és informatikai problémák megoldására, így konkrétan -- a nagybonyolultságú integrált áramkörök 2- és 3-dimenziós huzalozási kérdéseire (csatorna- vagy 'switchbox'-huzalozás, minimális összhosszúságú/területű/térfogatú huzalozás); -- hardware és software komponenseket egyaránt tartalmazó rendszerek szintézisére; -- távközlési hálózatok megbízhatóságának, szolgáltatás-minőségének növelésére; -- közlekedési hálózatok informatikai szolgáltatásaira (pl. haladó járművek adatai alapján a hálózat topológiájának vizsgálata, optimális útvonal javaslása); -- az adaptív elosztott multimédia szerver fejlesztésére; -- web oldalakon hatékonyabb kereső programmok készítésére. Eközben tiszta matematikai és számítástudományi eredményekhez is jutottunk, így konkrétan -- a gráfelméletben (összefüggőséget növelő kiegészítések, Hamilton-körök, gráf-izomorfia); -- a matroidelméletben (gyenge és erős leképezések); -- a kvantumszámításokban (periódikus függvények, rejtett részcsoportok); -- a paraméteres bonyolultságelméletben (gráfok és hipergráfok színezése és listaszínezése); -- rúdszerkezetek és ''tensegrity'' szerkezetek merevségének elméletében. | Methods of combinatorial optimization (algorithms for graphs and matroids, complexity considerations) were applied for various problems in electrical engineering and informatics, in particular -- for the detailed routing of 2- and 3-dimensional VLSI circuits (channel and switchbox routing, minimum length/area/volume routing); -- for hardware/software codesign; -- for improving the quality of service of telecommunication networks; -- for integrated traffic information services (e.g. map generation and route guidance from floating car data); -- for the developments of adaptive distributed multimedia servers; -- for designing more effective search algorithms in the web graph. During these studies we also obtained results in pure mathematics and in theoretical computer science as well, in particular -- in the theory of graphs (connectivity augmentations, Hamiltonian circuits, graph isomorphism); -- in the theory of matroids (strong and weak maps); -- in quantum computing (periodic functions, hidden subgroup properties); -- in parametrized complexity theory (colouring or list-colouring of graphs and hypergraphs); -- in the theory of rigidity of bar-and-joint and tensegrity frameworks

Alkalmazott algoritmusok nagyméretű feladatokra = Applied algorithms for large-scale problems

Alap és alkalmazott kutatást végeztünk a következő fő területeken: - Formális matematikai módszerek adatbányászatban és optimalizálásban; - Nagyméretű adatok elemzése és modellezése, hálózatokkal kapcsolatos üzleti intelligencia alkalmazásokban; - Felhasználó és tartalom összerendelése, keresés, ajánlás. A projekt résztvevői zárt láncban a teljes innovációs láncot lefedik az oktatástól (ELTE és BME algoritmusok, adatbányászat, Web információ-keresés előadások) az elméleti kutatásokon át az alkalmazásokig. A kutatáshoz kapcsolódó legfontosabb két ipari partnerünk a Magyar Telekom és az AEGON, amelyek számára egyedi kereső megoldásokat fejlesztettünk, naplóelemzési és ügyfél-elemzési feladatokat oldottunk meg. Európai kapcsolataink segítségével a jelen kutatási eredményekre épülő Digitális Könyvtárak és Biztonság témájú projektben veszünk részt. A kutatásunk nemzetközi elismertségét jelzi, hogy felkértek a legjelentősebb európai adatbányászati verseny, az ECML/PKDD Discovery Challenge szervezésére, illetve a legrangosabb World Wide Web konferencián Workshop Chair, a WSDM (Web Search and Data Mining) konferencián szenior, további kapcsolódó témájú konferencián és workshopon (ICALP, AIRWeb, ESA stb) programbizottági tagot adunk. Legfontosabb eredményeink: - Előrelépést a véges testek feletti polinomfelbontás algoritmusaiban; - Díjnyertes megoldás a KDD Cup 2009 feladaton; - Új Web Spam szűrő módszerek; - Tartalom alapú képkereső eljárások. | Our results cover a wide range of areas of theory and application: -Formal mathematical methods in data mining and optimization; -Analysis and modeling very large scale data with applications in the areas of network related business intelligence; -User-content interaction, optimization. The project team covers full innovation chain from Education (Technical University and Eötvös University courses in algorithms, data mining, Web information retrieval), Pure, Applied Research and Innovation. Our industrial exploitation include the Hungarian Telecom Group and AEGON Hungary where we developed custom search engines and conducted log mining and business intelligence projects. Based on the reported results, we participated in several Digital Libraries and Security ICT projects. Our results are acknowledged by being the main organizer of the major European data mining contest, the ECML/PKDD Discovery Challenge 2010 and the invitation to serve as Workshop Chair at the highest prestige World Wide Web conference, senoir program committee member at the Web Search and Data Mining conferences, and PC member of other related conferences and workshops (ICALP, AIRWeb, ESA etc). Our most important research results include -Breakthrough algorithms in factorization of polynomials over finite fields; -Prize winner solution at KDD Cup 2009, in a telco classification task; -New methodologies in Web Spam filtering; -Content-based multimedia indexing methods

The potential use of the Penicillium chrysogenum antifungal protein PAF, the designed variant PAFopt and its γ-core peptide Pγopt in plant protection

The prevention of enormous crop losses caused by pesticide-resistant fungi is a serious challenge in agriculture. Application of alternative fungicides, such as antifungal proteins and peptides, provides a promising basis to overcome this problem; however, their direct use in fields suffers limitations, such as high cost of production, low stability, narrow antifungal spectrum and toxicity on plant or mammalian cells. Recently, we demonstrated that a Penicillium chrysogenum-based expression system provides a feasible tool for economic production of P. chrysogenum antifungal protein (PAF) and a rational designed variant (PAFopt ), in which the evolutionary conserved γ-core motif was modified to increase antifungal activity. In the present study, we report for the first time that γ-core modulation influences the antifungal spectrum and efficacy of PAF against important plant pathogenic ascomycetes, and the synthetic γ-core peptide Pγopt , a derivative of PAFopt , is antifungal active against these pathogens in vitro. Finally, we proved the protective potential of PAF against Botrytis cinerea infection in tomato plant leaves. The lack of any toxic effects on mammalian cells and plant seedlings, as well as the high tolerance to harsh environmental conditions and proteolytic degradation further strengthen our concept for applicability of these proteins and peptide in agriculture

Solution Structure, Dynamics, and New Antifungal Aspects of the Cysteine-Rich Miniprotein PAFC

The genome of Penicillium chrysogenum Q176 contains a gene coding for the 88-amino-acid (aa)-long glycine- and cysteine-rich P. chrysogenum antifungal protein C (PAFC). After maturation, the secreted antifungal miniprotein (MP) comprises 64 aa and shares 80% aa identity with the bubble protein (BP) from Penicillium brevicompactum, which has a published X-ray structure. Our team expressed isotope (15N, 13C)-labeled, recombinant PAFC in high yields, which allowed us to determine the solution structure and molecular dynamics by nuclear magnetic resonance (NMR) experiments. The primary structure of PAFC is dominated by 14 glycines, and therefore, whether the four disulfide bonds can stabilize the fold is challenging. Indeed, unlike the few published solution structures of other antifungal MPs from filamentous ascomycetes, the NMR data indicate that PAFC has shorter secondary structure elements and lacks the typical β-barrel structure, though it has a positively charged cavity and a hydrophobic core around the disulfide bonds. Some parts within the two putative γ-core motifs exhibited enhanced dynamics according to a new disorder index presentation of 15N-NMR relaxation data. Furthermore, we also provided a more detailed insight into the antifungal spectrum of PAFC, with specific emphasis on fungal plant pathogens. Our results suggest that PAFC could be an effective candidate for the development of new antifungal strategies in agriculture