Bayesian models and algorithms for protein beta-sheet prediction

Prediction of the three-dimensional structure greatly benefits from the information related to secondary structure, solvent accessibility, and non-local contacts that stabilize a protein's structure. Prediction of such components is vital to our understanding of the structure and function of a protein. In this paper, we address the problem of beta-sheet prediction. We introduce a Bayesian approach for proteins with six or less beta-strands, in which we model the conformational features in a probabilistic framework. To select the optimum architecture, we analyze the space of possible conformations by efficient heuristics. Furthermore, we employ an algorithm that finds the optimum pairwise alignment between beta-strands using dynamic programming. Allowing any number of gaps in an alignment enables us to model beta-bulges more effectively. Though our main focus is proteins with six or less beta-strands, we are also able to perform predictions for proteins with more than six beta-strands by combining the predictions of BetaPro with the gapped alignment algorithm. We evaluated the accuracy of our method and BetaPro. We performed a 10-fold cross validation experiment on the BetaSheet916 set and we obtained significant improvements in the prediction accuracy

Bayesian models and algorithms for protein beta-sheet prediction

Prediction of the three-dimensional structure greatly benefits from the information related to secondary structure, solvent accessibility, and non-local contacts that stabilize a protein's structure. Prediction of such components is vital to our understanding of the structure and function of a protein. In this paper, we address the problem of beta-sheet prediction. We introduce a Bayesian approach for proteins with six or less beta-strands, in which we model the conformational features in a probabilistic framework. To select the optimum architecture, we analyze the space of possible conformations by efficient heuristics. Furthermore, we employ an algorithm that finds the optimum pairwise alignment between beta-strands using dynamic programming. Allowing any number of gaps in an alignment enables us to model beta-bulges more effectively. Though our main focus is proteins with six or less beta-strands, we are also able to perform predictions for proteins with more than six beta-strands by combining the predictions of BetaPro with the gapped alignment algorithm. We evaluated the accuracy of our method and BetaPro. We performed a 10-fold cross validation experiment on the BetaSheet916 set and we obtained significant improvements in the prediction accuracy

The management of foreign exchange risk with futures agreements in corporations: A derivative market practice

Dünyamız 2000'li yıllara giderek hızlanan küresellesme olgusu ile birlikte girmistir. Küresellesmeyle birlikte firmaların maruz kalabilecekleri çok çesitli risklerle karsı karsıya kalmıslardır. Bunların basında da devalüasyon riski ve parite riski gelmektedir. Bu tezin amacı; firmaların malî yapılarının, devalüasyon ve yurt dısı piyasalardaki çapraz kurlar (pariteler) gibi piyasa degiskenlerine olan hassasiyetin ölçülerek, malî yapı içerisindeki döviz kuru riski ve parite riskinin tespit edilmesi, tespit edilen risklerin firmaya uygun türev ürünler kullanılarak riskten korunma (hedging) yapılmasıdır. Ticarî hareketlerden yola çıkılarak risk yönetimi aktif ve pasif nakit akısları modeli hazırlanmıstır. Daha sonra da döviz riski yönetimi modeli olusturulmustur. Stratejik döviz pozisyonu, net döviz pozisyonu incelenerek açık ya da kapalı pozisyon tanımı yapılmıs, firmaların ticari hareketlerinin olusumu ve degisimine duyarlı iki temel döviz riski olan devalüasyon riski ve parite riskinin izlenmesi saglanmıstır. Tezin son asamasında ise, bu modelin kullanılmasıyla ilgili olarak; MKB de islem gören 27 tekstil firmasına örnek uygulama yapılmıs ve sonuçlar incelenerek tekstil sektörünün döviz riski yönetimi ile ilgili genel bir sonuç ortaya konmustur. Döviz riskinden korunmaları amacıyla VOB'da (Vadeli slemler ve Opsiyon Borsası) islem gören gelecek (futures) sözlesmelerinden alım-satım yapmaları önerilmistir. Globalization has started to influence our world faster than ever in the beginning of 21st century. With globalization, corporations have faced with a lot of different risks. At top of these risks are devaluation and parity risks. The main goal of this study is to evaluate sensitiveness of corporations? financial structures against devaluation and parity, determine foreign exchange rate and parity risk, and hedge corporation by using appropriate derivative market products. In this paper, assets and liability cash flow model has been prepared for risk management, which was done by tracking trading movements. After that, foreign exchange risk management model has been made. Open and close position have been defined by examining strategic and net foreign exchange position. In addition, devaluation and parity risks- the two main exchange rate risks- have been observed, which sensitive to corporations? trading movements. In the final section of this paper, the model has been practiced on 27 textile companies, the results investigated, and brought up a general result about managing exchange rate risk in textile sector. Finally, we have suggested these corporations to hedge themselves against exchange rate risk by using futures agreements

Intrasellar arachnoid cyst: A case report and review of the literature

AbstractIntroductionArachnoid cysts (ACs) are frequently found on intracranial imaging studies but intrasellar arachnoid cysts are rarely encountered.Presentation of caseWe present a 49-year old patient who had headaches for 6 months and cystic sellar mass was found in his cranial imaging. We operated him by transnasal transsphenoidal route. Our intraoperative diagnosis was an arachnoid cyst and pathologic studies verified our observation. He did well postoperatively and after a 1year follow-up he was left free from future follow-ups.DiscussionAs common cystic lesions occupying the sellar region can simulate ACs both clinically and radiologically, neurosurgeon can fail to include ACs in making the initial diagnosis preoperatively.ConclusionAlthough a rare entity, arachnoid cysts should be considered in the differential diagnosis of sellar region

Yetim proteinlerde ikincil yapı öngörüsü için eğitim kümesi indirgeme yöntemleri = Training set reduction methods for single sequence protein secondary structure prediction

Orphan proteins are characterized by the lack of significant sequence similarity to almost all proteins in the database. To infer the functional properties of the orphans, more elaborate techniques that utilize structural information are required. In this regard, the protein structure prediction gains considerable importance. Secondary structure prediction algorithms designed for orphan proteins (also known as single-sequence algorithms) cannot utilize multiple alignments or aligment profiles, which are derived from similar proteins. This is a limiting factor for the prediction accuracy. One way to improve the performance of a single-sequence algorithm is to perform re-training. In this approach, first, the models used by the algorithm are trained by a representative set of proteins and a secondary structure prediction is computed. Then, using a distance measure, the original training set is refined by removing proteins that are dissimilar to the initial prediction. This step is followed by the re-estimation of the model parameters and the prediction of the secondary structure. In this paper, we compare training set reduction methods that are used to re-train the hidden semi-Markov models employed by the IPSSP algorithm. We found that the composition based reduction method has the highest performance compared to the other reduction methods. In addition, threshold-based reduction performed bettern than the reduction technique that selects the first 80% of the dataset proteins

Evaluation of epicardial fat tissue thickness in patients with multiple sclerosis

Aim: Multiple sclerosis (MS), which is inflammatory in its pathogenesis, damages the myelin sheath in the central nervous system (CNS) and causes axonal loss. Epicardial fat tissue (EFT), located between the myocardium and the visceral layer of the pericardium, surrounds the heart and several inflammatory cytokines is secreted from this tissue. In this study, we aimed to investigate EFT thickness in MS patients and compared with that of volunteer non-MS subjects. Methods: A total of 154 subjects comprising 61 MS patients and 93 volunteers matched for gender and age were included in our study.  Epicardial fat tissue thickness was measured by echocardiography. All values were compared between groups. Results: Echocardiographic parameters were similar in both groups. However, the mean EFT thickness was significantly higher in the MS group than in the control group (p<0.001). Epicardial fat tissue thickness was also significantly correlated with the presence of MS (r=0.33, p<0.001). Conclusion: The results of our study suggest that the increase in epicardial adipose tissue thickness in MS patients may be a predictive factor for cardiovascular disease. However, the clinical significance of this finding and its relevance to MS pathogenesis should be investigated in further studies

Türk Katılım Sigortacılığı Sektörünün SD-Waspas Modeliyle Analizi

Sigorta sektörü, ülke ekonomilerinin gelişmesinde hayati bir rol oynamaktadır. Sermaye piyasasının ve ekonomik altyapının gelişmesi için uzun vadeli tasarruf sağlayan ve kaynak yaratan, dolayısıyla ekonominin büyümesine istikrar sağlayan bir sektördür. Bu çalışmada ülkemizde son yıllarda önemli bir büyüme trendi yakalayarak gelişme gösteren, toplam sigortacılık prim üretimi içerisindeki payı her geçen gün artan katılım sigortacılığı sektörünün 2021 yılı 4 çeyrek dönem performanslarının hibrit bir çok kriterli karar verme (ÇKKV) yöntemi ile değerlendirilmesi amaçlanmıştır. Bu amaçla ilk olarak SD ağırlıklandırma yöntemi ile kriterlere ait önem ağırlıkları belirlendikten sonra WASPAS yöntemi ile alternatifler sıralanmıştır. Analiz sonucunda katılım sigorta şirketlerinin performansının belirlenmesinde genel olarak en önemli kriterin kısa vadeli borçlar / toplam aktifler kriteri olduğu tespit edilmiştir. Bereket Katılım Hayat A.Ş.’nin ele alınan dönemlerde istikrarlı bir şekilde finansal performans sıralamasında ilk sırada yer aldığı tespit edilmiştir

Determining the cognitive structres of the middle school and high school students related to the “music teachers” concept through word association test

Çalışmada, veri toplama aracı olarak Kelime İlişkilendirme Testi kullanılmıştır. Veriler içerik analizi yoluyla çözümlenmiştir. Çalışmaya 2017-2018 öğretim yılı bahar döneminde İzmir Selçuk Şehit Ömer Halis İMKB Anadolu Lisesi ve İsa Bey Ortaokulu’nda müzik dersini alan 210 öğrenci katılmıştır. Öğrencilerin “müzik öğretmeni” ile ilgili 1 dakika içerisinde akıllarına gelen ilk beş cevap kelimeyi yazmaları ve ardından bu kelimelerle ilgili bir cümle kurmaları istenmiştir. Araştırmada kavramlara ilişkin elde edilen kelimeler ayrıntılı olarak incelenmiştir. Test sonuçlarından elde edilen veriler kategorilere ayrılarak frekans tabloları oluşturulmuştur. Öğrencilerin “müzik öğretmeni” kavramına yönelik en çok kullandıkları kelimeler tespit edilmiş ve yedi kategori olarak belirlenerek frekans değerleri verilmiştir.Being a qualitative research, this study was executed to identify secondary school and high school students’ cognitive structure oriented to “music teacher” concept. In the study, Word Association Test was used as data collection tool. Data was processed with content analysis method. 210 students who took music class in İzmir Selçuk Şehit Ömer Halis Demir İMKB Anadolu High School and İsa Bey Ortaokulu in spring term of 2017-2018 school year participated in the study. Students were asked to write the first five words they think of about “music teacher” in one minute and then to form a sentence about these words. In the research, obtained words concerning the concepts were studied in detail. Data obtained from test results were categorized and frequency tables were formed. The most used words by students oriented to “music teacher” concept were identified, then classified as seven categories and frequency values were given

The efficacy of albendazole treatment in a patient with hydatid cyst disease of multiorgan involvement

Hydatid cyst disease, which is caused by echinococcusgranulosus still poses a serious problem in endemic areas.The disease frequently involves liver and lung. Otherorgan involvements are rare. In a 18-year old patient, bilaterallung, right ventricle of heart, liver and spleen involvementwere detected. With albendazole treatmentcyst in heart was completely disappeared, and liver cystwas found to be decreased in size. However, no declinein the number and size of cysts in lung was observed.Therefore, it was concluded that albendazole may not beeffective in pulmonary hydatid disease compared to otherorgans.Key words: Albendazole, hydatid cyst, multiorgan involvemen