Browsing by Author "Sefer, Emre"
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Asset price and direction prediction via deep 2D transformer and convolutional neural networks
Tuncer, Tuna; Kaya, Uygar; Sefer, Emre; Alacam, Onur; Hoşer, Tuğcan (ACM, 2022-11-02)Artificial intelligence-based algorithmic trading has recently started to attract more attention. Among the techniques, deep learning-based methods such as transformers, convolutional neural networks, and patch embedding ... -
BERT2OME: Prediction of 2′-O-methylation modifications from RNA sequence by transformer architecture based on BERT
Soylu, Necla Nisa; Sefer, Emre (IEEE, 2023-06)Recent work on language models has resulted in state-of-the-art performance on various language tasks. Among these, Bidirectional Encoder Representations from Transformers (BERT) has focused on contextualizing word embeddings ... -
BioCode: A data-driven procedure to learn the growth of biological networks
Sefer, Emre (IEEE, 2022-11)Probabilistic biological network growth models have been utilized for many tasks including but not limited to capturing mechanism and dynamics of biological growth activities, null model representation, capturing anomalies, ... -
A comparison of topologically associating domain callers over mammals at high resolution
Sefer, Emre (BioMed Central Ltd, 2022-04-12)Background: Topologically associating domains (TADs) are locally highly-interacting genome regions, which also play a critical role in regulating gene expression in the cell. TADs have been first identified while investigating ... -
Hi–C interaction graph analysis reveals the impact of histone modifications in chromatin shape
Sefer, Emre (Springer, 2021-07-17)Chromosome conformation capture experiments such as Hi–C map the three-dimensional spatial organization of genomes in a genome-wide scale. Even though Hi–C interactions are not biased towards any of the histone modifications, ... -
Joint modeling of histone modifications in 3D genome shape through Hi-C interaction graph
Sefer, Emre (Springer, 2021)Chromosome conformation capture experiments such as Hi-C are used to map the three-dimensional spatial organization of genomes. Even though Hi-C interactions are not biased towards any of the histone modifications, previous ... -
Metric labeling and semimetric embedding for protein annotation prediction
Sefer, Emre; Kingsford, C. (Mary Ann Liebert, Inc., 2021-05-01)Computational techniques have been successful at predicting protein function from relational data (functional or physical interactions). These techniques have been used to generate hypotheses and to direct experimental ... -
MOCMIN: convex inferring of modular low-rank contact networks over COVID diffusion data
Sefer, Emre (TÜBİTAK, 2022)SEIR (which consists of susceptible, exposed, infected, and recovered states) is a common diffusion model which could model different disease propagation dynamics across various domains such as influenza and COVID diffusion. ... -
A novel GBT-based approach for cross-channel fraud detection on real-world banking transactions
Dolu, U.; Sefer, Emre (IEEE, 2022)The most recent research on hundreds of financial institutions uncovered that only 26 % of them have a team assigned to detect cross-channel fraud. Due to the developing technologies, various fraud techniques have emerged ... -
A novel sampling technique and gradient boosting tree-based approach for cross-channel fraud detection
The most recent research on hundreds of financial institutions uncovered that only 26% of them have a team assigned to detect cross-channel fraud. Due to the developing technologies, various fraud techniques have emerged ... -
ProbC: joint modeling of epigenome and transcriptome effects in 3D genome
Sefer, Emre (BioMed Central Ltd, 2022-12)Background: Hi-C and its high nucleosome resolution variant Micro-C provide a window into the spatial packing of a genome in 3D within the cell. Even though both techniques do not directly depend on the binding of specific ...
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