Browsing by Author "Demirci, Yilmaz Mehmet"

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Citation - WoS: 24
Citation - Scopus: 24
Circular RNA-MicroRNA Interaction Predictions in SARS-CoV Infection
(Walter de Gruyter Gmbh, 2021) Demirci, Yilmaz Mehmet; Demirci, Muserref Duygu Sacar; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
Different types of noncoding RNAs like MicroRNAs (miRNAs) and circular RNAs (circRNAs) have been shown to take part in various cellular processes including post-transcriptional gene regulation during infection. MiRNAs are expressed by more than 200 organisms ranging from viruses to higher eukaryotes. Since miRNAs seem to be involved in host-pathogen interactions, many studies attempted to identify whether human miRNAs could target severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mRNAs as an antiviral defence mechanism. In this work, a machine learning based miRNA analysis work flow was developed to predict differential expression patterns of human miRNAs during SARS-CoV-2 infection. In order to obtain the graphical representation of miRNA hairpins, 36 features were defined based on the secondary structures. Moreover, potential targeting interactions between human circRNAs and miRNAs as well as human miRNAs and viral mRNAs were investigated.
Comprehensive Prediction of FBN1 Targeting miRNAs: A Systems Biology Approach for Marfan Syndrome
(Galenos Publ House, 2025) Orhan, Mehmet Emin; Demirci, Yilmaz Mehmet; Demirci, Muserref Duygu Sacar; 02.01. Mühendislik Bilimleri; 01. Abdullah Gül University; 02. Mühendislik Fakültesi; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
Objective: Marfan syndrome (MFS) is a genetic connective tissue disorder primarily caused by mutations in the FBN1 gene. Emerging evidence highlights the regulatory role of microRNAs (miRNAs) in modulating gene expression in MFS, but a systematic investigation into miRNAs targeting FBN1 is lacking. This study aimed to comprehensively identify miRNAs interacting with the FBN1 transcript to reveal potential molecular regulators and therapeutic targets. Methods: Human miRNA sequences were retrieved from miRBase (Release 22.1), and the canonical FBN1 transcript (RefSeq: NM_000138.5) was used for target prediction. Computational interaction analysis was conducted using the psRNATarget server with stringent parameters to detect potential miRNA binding sites. Expression profiles and disease associations of the top candidate miRNAs were further investigated through database integration and literature review. Results: Out of 2656 human mature miRNAs analyzed, 251 were predicted to bind FBN1, with the hsa-miR-181 family exhibiting the highest number of predicted interactions. Evidence from the literature highlighted dysregulation of hsa-miR-181 expression in MFS patients, suggesting a functional role in disease pathophysiology. Conclusion: This study identifies key members of the hsa-miR-181 family as post-transcriptional regulators of FBN1, offering new insights into miRNA-driven mechanisms in MFS. These findings support the potential of RNA-based diagnostics and therapeutic strategies targeting miRNA-FBN1 interactions.
Citation - WoS: 2
Citation - Scopus: 2
NeRNA: A Negative Data Generation Framework for Machine Learning Applications of Noncoding RNAs
(Pergamon-Elsevier Science Ltd, 2023) Orhan, Mehmet Emin; Demirci, Yilmaz Mehmet; Demirci, Mueserref Duygu Sacar; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
Many supervised machine learning based noncoding RNA (ncRNA) analysis methods have been developed to classify and identify novel sequences. During such analysis, the positive learning datasets usually consist of known examples of ncRNAs and some of them might even have weak or strong experimental validation. On the contrary, there are neither databases listing the confirmed negative sequences for a specific ncRNA class nor standardized methodologies developed to generate high quality negative examples. To overcome this challenge, a novel negative data generation method, NeRNA (negative RNA), is developed in this work. NeRNA uses known examples of given ncRNA sequences and their calculated structures for octal representation to create negative sequences in a manner similar to frameshift mutations but without deletion or insertion. NeRNA is tested individually with four different ncRNA datasets including MicroRNA (miRNA), transfer RNA (tRNA), long noncoding RNA (lncRNA), and circular RNA (circRNA). Furthermore, a species-specific case analysis is per-formed to demonstrate and compare the performance of NeRNA for miRNA prediction. The results of 1000 fold cross-validation on Decision Tree, Naive Bayes and Random Forest classifiers, and deep learning algorithms such as Multilayer Perceptron, Convolutional Neural Network, and Simple feedforward Neural Networks indicate that models obtained by using NeRNA generated datasets, achieves substantially high prediction performance. NeRNA is released as an easy-to-use, updatable and modifiable KNIME workflow that can be downloaded with example datasets and required extensions. In particular, NeRNA is designed to be a powerful tool for RNA sequence data analysis.
Citation - WoS: 1
Citation - Scopus: 2
On a Class of Harada Rings
(De Gruyter Poland Sp. z o.o., 2022) Turkmen, Burcu Nisanci; Demirci, Yilmaz Mehmet; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi
In this study, inspired by the definition and a previous study [F. Eryilmaz, SS -lifting modules and rings, Miskolc Math. Notes 22 (2021), no. 2, 655-662], left Harada rings are adapted to ss-Harada rings, and the important properties of these rings are provided. The characterization of a left ss-Harada ring R with R left perfect and Rad(R) included in Soc(RR) was found with the help of strongly local R-modules.
Citation - WoS: 2
Citation - Scopus: 2
On Rings With One Middle Class of Injectivity Domains
(Univ Osijek, dept Mathematics, 2022) Alizade, Rafail; Demirci, Yilmaz Mehmet; Turkmen, Burcu Nisanci; Turkmen, Ergul; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi
A module M is said to be modest if the injectivity domain of M is the class of all crumbling modules. In this paper, we investigate the basic properties of modest modules. We provide characterizations of some classes of rings using modest modules. In particular, we show that a ring having the class of crumbling modules as the only right middle class of injectivity domains is either a right V-ring or right Noetherian; and a commutative ring with this property is regular. We also give criteria for a ring having the class of crumbling modules as the only right middle class of injectivity domains.
Citation - WoS: 5
Citation - Scopus: 5
Rings With Modules Having a Restricted Injectivity Domain
(Springer International Publishing AG, 2020) Demirci, Yilmaz Mehmet; Turkmen, Burcu Nisanci; Turkmen, Ergul; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi
We introduce modules whose injectivity domains are contained in the class of modules with zero radical and call them working-class. This notion gives a generalization of poor modules that have minimal injectivity domain. Semisimple working-class modules always exist for arbitrary rings whereas their predecessors do not. We investigate the rings over which every module is either injective or working-class. Right weakly V-rings are examples of these rings. Moreover, we study the existence of working-class simple modules and show that if there is a projective working-class simple right module, then the ring is a right GV-ring.
Rings With Variations of Flat Covers
(Honam Mathematical Soc, 2019) Demirci, Yilmaz Mehmet; Turkmen, Ergul; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi
We introduce flat e-covers of modules and define e-perfect rings as a generalization of perfect rings. We prove that a ring is right perfect if and only if it is semilocal and right e-perfect which generalizes a result due to N. Ding and J. Chen. Moreover, in the light of the fact that a ring R is right perfect if and only if flat covers of any R-module are projective covers, we study on the rings over which flat covers of modules are (generalized) locally projective covers, and obtain some characterizations of (semi) perfect, A-perfect and B-perfect rings.
RNA İkincil Yapılarının Çok Boyutlu Gösterimi ve Pre-Mirna Tespiti Için Uygulamaları
(TUBİTAK, 2021) Saçar Demirci, Müşerref Duygu; Demirci, Yilmaz Mehmet; 0000-0003-2012-0598; 0000-0003-3802-4211; AGÜ, Yaşam ve Doğa Bilimleri Fakültesi, Biyomühendislik Bölümü; Saçar Demirci, Müşerref Duygu; Demirci, Yilmaz Mehmet; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi; 04. Yaşam ve Doğa Bilimleri Fakültesi; 04.01. Biyomühendislik
MikroRNA'lar (miRNA'lar), transkripsiyon sonrası gen ekspresyonu düzenleyicileridir. Bir_x000D_ miRNA yüzlerce haberci RNA'yı (mRNA'lar) hedefleyebildiği gibi, bir mRNA farklı miRNA'lar_x000D_ tarafından hedeflenebilir, üstelik tek bir miRNA bir mRNA sekansında çeşitli bağlanma_x000D_ bölgelerine sahip olabilir. Bu nedenle miRNA'ları deneysel olarak araştırmak oldukça_x000D_ karmaşıktır. Bu tür zorlukları aşabilmek için makine öğrenimi (ML) sıklıkla kullanılmaktadır._x000D_ ML analizinin temel kısımları büyük ölçüde giriş verilerinin kalitesine ve verileri tanımlayan_x000D_ özelliklerin kapasitesine bağlıdır. Daha önce miRNA'lar için 1000'den fazla özellik önerilmişti._x000D_ Bu projede, RNA ikincil yapısını temsil eden yeni özellikler ve yüksek doğruluk değerleri_x000D_ sağlayan, dinamik, çok boyutlu grafik gösterimini tanımlamayı hedeflemiştik. Bu çalışmada,_x000D_ ML tabanlı miRNA tahmini için yeni ve kolayca güncellenebilir bir yaklaşım geliştirilmiştir._x000D_ Bilinen insan miRNA'larının ve sözde saç tokalarının random forest (RF), support vector_x000D_ machine (SVM) ve multilayer perceptron (MLP) gibi çeşitli sınıflandırıcılarla_x000D_ sınıflandırılmasıyla binlerce model oluşturulmuştur. Yöntem insan verilerine dayanarak_x000D_ oluşturulmuş olsa da en iyi model miRBase ve MirGeneDB gibi kamu veri tabanlarından_x000D_ insan olmayan saç tokaları üzerinde test edilmiş ve yüksek skorlar üretilmiştir. Ayrıca,_x000D_ yöntemin farklı veriler üzerindeki etkinliğini göstermek için ekspresyon farkları tahmini_x000D_ (differential expression prediction) analizinde de kullanılmıştır. Bu aşamada SARS-CoV-2_x000D_ enfeksiyonunun etkisini ölçen bir veri setinin analizinden elde edilen sonuçlar yayınlanmıştır.
Citation - WoS: 1
Citation - Scopus: 2
WSA-Supplements and Proper Classes
(MDPI, 2022) Demirci, Yilmaz Mehmet; Turkmen, Ergul; 01. Abdullah Gül University; 02.01. Mühendislik Bilimleri; 02. Mühendislik Fakültesi
In this paper, we introduce the concept of wsa-supplements and investigate the objects of the class of short exact sequences determined by wsa-supplement submodules, where a submodule U of a module M is called a wsa-supplement in M if there is a submodule V of M with U + V = M and U boolean AND V is weakly semiartinian. We prove that a module M is weakly semiartinian if and only if every submodule of M is a wsa-supplement in M. We introduce CC-rings as a generalization of C-rings and show that a ring is a right CC-ring if and only if every singular right module has a crumbling submodule. The class of all short exact sequences determined by wsa-supplement submodules is shown to be a proper class which is both injectively and co-injectively generated. We investigate the homological objects of this proper class along with its relation to CC-rings.