A5088913912- Complex Network Analysis Techniques
- Graph theory and applications
- Opinion Dynamics and Social Influence
- Matrix Theory and Algorithms
- Hedgehog Signaling Pathway Studies
- Esophageal Cancer Research and Treatment
- Esophageal and GI Pathology
- SARS-CoV-2 detection and testing
- Sparse and Compressive Sensing Techniques
- Random Matrices and Applications
- Cancer, Stress, Anesthesia, and Immune Response
- Stochastic Gradient Optimization Techniques
- VLSI and FPGA Design Techniques
- Epigenetics and DNA Methylation
- Fuel Cells and Related Materials
- Image and Signal Denoising Methods
- Face and Expression Recognition
- Sustainability and Ecological Systems Analysis
- Tissue Engineering and Regenerative Medicine
- Cooperative Communication and Network Coding
- Slime Mold and Myxomycetes Research
- Biosensors and Analytical Detection
- Statistical and numerical algorithms
- Advanced Graph Neural Networks
- Machine Learning and Algorithms
Kent State University
2018-2024
King Saud University
2024
Washington University in St. Louis
2014
Université de Perpignan
1999
We report a biomarker-based non-endoscopic method for detecting Barrett's esophagus (BE) based on methylated DNAs retrieved via swallowable balloon-based esophageal sampling device. BE is the precursor of, and major recognized risk factor for, developing adenocarcinoma. Endoscopy, current standard detection, not cost-effective population screening. performed genome-wide screening to ascertain regions targeted recurrent aberrant cytosine methylation in BE, identifying high-frequency within...
This paper discusses and develops new methods for fitting trigonometric curves, such as circles, ellipses, dumbbells, to data points in the plane. Available circles or ellipses are very sensitive outliers data, time consuming when number of is large. The present focuses on curve that attractive use We propose a direct method two iterative dumbbell curves based polynomials. These efficiently minimize sum squared geometric distances between given fitted curves. In particular, we interested...
In many real world problems it is of interest to ascertain which factors are most relevant for determining a given outcome. This the so-called variable selection problem. The present paper proposes new regression model its solution. We show that proposed satisfies continuity, sparsity, and unbiasedness properties. A generalized Krylov subspace method practical solution minimization problem involved described. can be used both small-scale large-scale problems. Several computed examples...
Chronic stimulation of α 1A -adrenergic receptors (α -ARs) is known to mediate therapeutic effects in animal heart failure models. To investigate the chronic -AR human cardiomyocytes, we tested engineered tissue (EHT) created with iPSC-derived cardiomyocytes. RNA-seq analysis confirmed EHT expressed -ARs. (2 wk) A61603 (10 nM) increased length-dependent activation (LDA) contraction. might be beneficial for treating by restoring LDA.
Over the last decades, learning methods using kernels have become very popular. The main reason is that real data analysis often requires nonlinear to detect dependencies allow successful predictions of properties interest. Gaussian been used in many studies such as algorithms and analysis. Most these shown parameter chosen for a kernel could huge impact on desired results. Therefore, it essential understand this theoretical level. contribution paper study effect bandwidth how well an...
Prior research on pool testing focus developing methods with the main objective of reducing total number tests. However, can also be used to improve accuracy process. The this paper is using same tests as that individual taking into consideration probability errors and multiplicity classification thresholds. Statistical models are developed evaluate impact classiffcation thresholds receiver operating characteristic (ROC) curve area under (AUC). findings indicate certain conditions, yields...
Premature infants suffering from respiratory dysfunction are often administered glucocorticoids (GCs) to mature the lungs. Unfortunately, neonates exposed GCs can exhibit neuromotor deficits and selective cerebellar stunting. In order test safety of GCs, we synthetic GC dexamethasone neonatal mouse pups found it potently increased apoptosis in external granule layer (EGL) cerebellum. The EGL is responsible for producing over 90% neurons cerebellum, which represents half entire brain. We...
There is a great interest in Hedgehog signaling both for its role cerebellar development and medulloblastoma (MB) treatment. The cerebellum maintains own proliferative layer called the external granule (EGL) that produces over 90% of neurons. During development, established dogma views as robust mitogenic stimulator EGL proliferation. However, other regions body, stimulation acts survival signal by potently inducing NPC apoptosis when lost. In this manner, sonic hedgehog ligand's...
Background: Transverse tubules (TT) are tunnel-like extensions of sarcolemma studded with ion channels coupling excitation, through the cytoplasm, to contraction in sarcomere matured cardiomyocytes (CMs). Expression timing sub-cellular TT-related genes (TT-rgs) individual human iPSC-derived CMs (hiPSC-CMs) has not yet been reported. Objective: Map out gene program TT-rgs by locations during hiPSC-CM differentiation using single-cell transcriptomics (scRNA Seq.). Methods: hiPSC-CMs were...
Background: Adrenergic receptors (AR) in an individual cardiomyocyte (CM) are not uniformly expressed at the single-cell level (Myagmar et al., 2017). The timing and cellular distribution of AR signaling (ARS) genes human iPSC-derived CMs (hiPSC-CMs) have yet been reported. Objective: To map out transcription program ARS during hiPSC-CM myogenesis using transcriptomics (scRNA Seq.). Methods: 132 CM curated by Kyoto Encyclopedia Genes Genomes were studied. derived from 2 commercially...
Matrix functions play an important role in applied mathematics. In network analysis, particular, the exponential of adjacency matrix associated with a provides valuable information about connectivity, as well relative importance or centrality nodes. Another popular approach to rank nodes is compute left Perron vector for network. The present article addresses problem evaluating functions, computing approximation vector, when only some columns and/or rows are known. Applications analysis...