Browsing by Author "Çiçek, A. Ercüment"
Now showing items 1-20 of 25
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AMULET: a novel read count-based method for effective multiplet detection from single nucleus ATAC-seq data
(BioMed Central Ltd., 2021-12)Detecting multiplets in single nucleus (sn)ATAC-seq data is challenging due to data sparsity and limited dynamic range. AMULET (ATAC-seq MULtiplet Estimation Tool) enumerates regions with greater than two uniquely aligned ... -
Apollo: A sequencing-technology-independent, scalable and accurate assembly polishing algorithm
(Oxford University Press, 2020-03)Motivation: Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject’s genome), which is further ... -
DeepND: Deep multitask learning of gene risk for comorbid neurodevelopmental disorders
(Cell Press, 2022-07-08)Autism spectrum disorder and intellectual disability are comorbid neurodevelopmental disorders with complex genetic architectures. Despite large-scale sequencing studies, only a fraction of the risk genes was identified ... -
Detailed modeling of positive selection improves detection of cancer driver genes
(Nature Publishing Group, 2019-07)Identifying driver genes from somatic mutations is a central problem in cancer biology. Existing methods, however, either lack explicit statistical models, or use models based on simplistic assumptions. Here, we present ... -
The effect of kinship in re-identification attacks against genomic data sharing beacons
(NLM (Medline), 2020-12)Motivation: Big data era in genomics promises a breakthrough in medicine, but sharing data in a private manner limit the pace of field. Widely accepted ‘genomic data sharing beacon’ protocol provides a standardized and ... -
Genetic circuits combined with machine learning provides fast responding living sensors
(Elsevier BV, 2021-04-15)Whole cell biosensors (WCBs) have become prominent in many fields from environmental analysis to biomedical diagnostics thanks to advanced genetic circuit design principles. Despite increasing demand on cost effective and ... -
An integrated genomic and metabolomic approach for defining survival time in adult oligodendrogliomas patients
(Springer, 2019)Introduction The identification of frequent acquired mutations shows that patients with oligodendrogliomas have divergent biology with differing prognoses regardless of histological classification. A better understanding ... -
k-Shell decomposition reveals structural properties of the gene coexpression network for neurodevelopment
(TÜBİTAK, 2017)Neurodevelopment is a dynamic and complex process, which involves interactions of thousands of genes. Understanding the mechanisms of brain development is important for uncovering the genetic architectures of neurodevelopmental ... -
Matrix Metalloproteinase-11 promotes early mouse mammary gland tumor growth through metabolic reprogramming and increased IGF1/AKT/FoxO1 signaling pathway, enhanced ER stress and alteration in mitochondrial UPR
(MDPI AG, 2020-08)Matrix metalloproteinase 11 (MMP11) is an extracellular proteolytic enzyme belonging to the matrix metalloproteinase (MMP11) family. These proteases are involved in extracellular matrix (ECM) remodeling and activation of ... -
Metabolomic profiling highlights the metabolic bases of acute-on-chronic and post-hepatectomy liver failure
(Elsevier, 2019)Background Posthepatectomy liver failure (PHLF) is the main limitation to extending liver resection but its pathophysiology is not yet fully understood. The aim of the study was to describe the metabolic adaptations that ... -
Metabolomics of small intestine neuroendocrine tumors and related hepatic metastases
(MDPI AG, 2019-12)To assess the metabolomic fingerprint of small intestine neuroendocrine tumors (SI-NETs) and related hepatic metastases, and to investigate the influence of the hepatic environment on SI-NETs metabolome. Ninety-four tissue ... -
Polishing copy number variant calls on exome sequencing data via deep learning
(NLM (Medline), 2022-06-13)Accurate and efficient detection of copy number variants (CNVs) is of critical importance owing to their significant association with complex genetic diseases. Although algorithms that use whole-genome sequencing (WGS) ... -
Potpourri: an epistasis test prioritization algorithm via diverse SNP selection
(Springer, 2020)Genome-wide association studies explain a fraction of the underlying heritability of genetic diseases. Investigating epistatic interactions between two or more loci help closing this gap. Unfortunately, sheer number of ... -
Predicting carbon spectrum in Heteronuclear Single Quantum Coherence Spectroscopy for online feedback during surgery
(IEEE, 2020)1H High-Resolution Magic Angle Spinning (HRMAS) Nuclear Magnetic Resonance (NMR) is a reliable technology used for detecting metabolites in solid tissues. Fast response time enables guiding surgeons in real time, for ... -
Revisiting the complex architecture of ALS in Turkey: expanding genotypes, shared phenotypes, molecular networks, and a public variant database
(John Wiley and Sons, 2020)The last decade has proven that amyotrophic lateral sclerosis (ALS) is clinically and genetically heterogeneous, and that the genetic component in sporadic cases might be stronger than expected. This study investigates ... -
Robust inference of kinase activity using functional networks
(Nature Publishing Group, 2021-02-19)Mass spectrometry enables high-throughput screening of phosphoproteins across a broad range of biological contexts. When complemented by computational algorithms, phospho-proteomic data allows the inference of kinase ... -
SPADIS: An algorithm for selecting predictive and diverse SNPs in GWAS
(IEEE, 2021)Phenotypic heritability of complex traits and diseases is seldom explained by individual genetic variants identified in genome-wide association studies (GWAS). Many methods have been developed to select a subset of variant ... -
SplitGuard: Detecting and mitigating training-hijacking attacks in split learning
(Association for Computing MachineryNew YorkNYUnited States, 2022-11-07)Distributed deep learning frameworks such as split learning provide great benefits with regards to the computational cost of training deep neural networks and the privacy-aware utilization of the collective data of a group ... -
ST-Steiner: a spatio-temporal gene discovery algorithm
(Oxford University Press, 2019)Motivation: Whole exome sequencing (WES) studies for autism spectrum disorder (ASD) could identify only around six dozen risk genes to date because the genetic architecture of the disorder is highly complex. To speed the ... -
A statistical framework for mapping risk genes from de novo mutations in whole-genome-sequencing studies
(Cell Press, 2018)Analysis of de novo mutations (DNMs) from sequencing data of nuclear families has identified risk genes for many complex diseases, including multiple neurodevelopmental and psychiatric disorders. Most of these efforts have ...
