Publications by authors named "Mohammad Shoyaib"

The silver pride of Bangladesh, migratory shad, Tenualosa ilisha (Hilsa), makes the highest contribution to the total fish production of Bangladesh. Despite its noteworthy contribution, a well-annotated transcriptome data is not available. Here we report a transcriptomic catalog of Hilsa, constructed by assembling RNA-Seq reads from different tissues of the fish including brain, gill, kidney, liver, and muscle.

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With the advent of high-throughput technologies, life sciences are generating a huge amount of varied biomolecular data. Global gene expression profiles provide a snapshot of all the genes that are transcribed in a cell or in a tissue under a particular condition. The high-dimensionality of such gene expression data (i.

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Texture-based analysis of images is a very common and much discussed issue in the fields of computer vision and image processing. Several methods have already been proposed to codify texture micro-patterns (texlets) in images. Most of these methods perform well when a given image is noise-free, but real world images contain different types of signal-independent as well as signal-dependent noises originated from different sources, even from the camera sensor itself.

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Article Synopsis
  • Eukaryotic promoter prediction is a challenging aspect of computational genomics, crucial for understanding genetic regulatory networks, and requires improved tools due to the growing sequence data.
  • A novel method is introduced that utilizes 128 unique DNA motifs and a Support Vector Machine (SVM) to effectively differentiate between promoter and non-promoter sequences across various organisms, achieving high accuracy rates and low false positives.
  • The study concludes that using 4-mer frequencies along with machine learning can significantly enhance the identification of RNA polymerase II promoters compared to existing methods.
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