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Combining multiple clustering and network analysis for discoveries in gene expression data
(Association for Computing Machinery, Inc, 2021)Clustering is a challenging research task which could benefit a wide range of practical applications, including bioinformatics. It targets success by optimizing a number of objectives, a characteristic mostly ignored by ... -
Using Johnson's SU distribution for modeling the background activity in extracellular neural recordings
(Institute of Electrical and Electronics Engineers Inc., 2021)Extracellular neural recordings obtained from awake behaving subjects through chronically implanted microelectrode arrays provide information about the functioning of the brain with sub-millisecond temporal resolution at ... -
A python code for maximum likelihood estimation of the location and scale parameters of the truncated normal distribution
(Institute of Electrical and Electronics Engineers Inc., 2021)Extracellular neural recordings obtained from chronically implanted microelectrode arrays are widely used in behavioral neurophysiology and invasive brain-machine interfaces. After the raw recordings are band-pass filtered ... -
Total internal reflection holographic microscopy for cellular imaging
(SPIE, 2022)The study of interfacial structures is of utmost importance not only for various research fields such as cell biology and display systems but also their sub-disciplines. One of the traditional means of imaging buried ... -
Maskless lithography with holographic feedback for the fabrication of optical elements
(SPIE, 2022)Photolithography has become a powerful tool in the fabrication of micro-optical elements following the advancements in grayscale approaches. However, hitting tight design tolerance goals require precise control of all ... -
An integrated top-stage incubator and lens free holographic imaging system for culture monitoring applications
(SPIE, 2022)Lens free inline holographic microscopy was shown to be a potent approach for many applications relying on cellular imaging. Applications requiring a large field of view at moderate resolution are the ones that are most ... -
Brain tumor classification using MRI images and convolutional neural networks
(Institute of Electrical and Electronics Engineers Inc., 2022)The brain tumor has become one of the most prominent types of cancers affecting a huge population across the globe every year. It has the lowest life expectancy rate and the risk of death is highly associated with the type, ... -
rs-fMRI analysis using spatio-temporal sparse convolutional neural networks
(Institute of Electrical and Electronics Engineers Inc., 2022)Neuropsychiatric diseases such as Autism Spectrum Disorder (ASD) and Schizophrenia cause various behavioral and communication dysfunctions in human life. Resting state functional magnetic resonance imaging (rs-fMRI) is ...