This dataset includes 70 sets of 3D confocal high-resolution images. All images were imaged using an LSM800 Zeiss microscope with a Plan-apochromat 1.40-NA, 63× objective, and Zeiss ZEN Blue 2.6 software was used to acquire the images. Three channels were used to acquire transmitted light (TL), SYBR GoldTM- (Thermo Fisher Scientific, Inc.) labeled (nuclear and mitochondrial DNA), and TMRM-labeled (mitochondria) images. Each confocal image consists of 32 slices with an interval of 0.15 µm and a YX resolution of 917 × 917 pixels.

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This study presented six datasets for DNA/RNA sequence alignment for one of the most common alignment algorithms, namely, the Needleman–Wunsch (NW) algorithm. This research proposed a fast and parallel implementation of the NW algorithm by using machine learning techniques. This study is an extension and improved version of our previous work . The current implementation achieves 99.7% accuracy using a multilayer perceptron with ADAM optimizer and up to 2912 giga cell updates per second on two real DNA sequences with a of length 4.1 M nucleotides.

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