Tausif Rehman

Muhammad nawaz Shareef university of agriculture Multan, CS/It, Graduate Student

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Deep-RPA: Vulnerability Classification of a Genome for CRISPR/Cas9 Off-targets

Current Bioinformatics

Background: Researchers working in genome engineering are making fast strides to precising the te... more Background: Researchers working in genome engineering are making fast strides to precising the techniques of site-specific gene editing. CRISPR-Cas (Clustered Regularly Interspaced Short Palindromic Repeats) is one of the most recent gene editing techniques. It consists of a Cas9 nuclease and a single guided RNA (sgRNA) that targets DNA at the required target site. Consequently, along with on-targets, genomes may also have multiple off-targets, which is a potential drawback of gene editing techniques. Lab-based assays are used to examine the off-target effects of sgRNA. This challenge makes the technique questionable in terms of cost, time and efficacy. Deep learning techniques have been used efficiently to analyze biological data and calculate off-target sites in the genome. This research aims to identify CRISPR off-targets within the genome as well as predict genome vulnerability for unexpected mutations using a deep learning approach. Method: This study presents a two-step data p...

Dataset of Pakistan Sign Language and Automatic Recognition of Hand Configuration of Urdu Alphabet through Machine Learning

Data in Brief, 2021

Social correspondence is one of the most significant columns that the public dependent on. Notabl... more Social correspondence is one of the most significant columns that the public dependent on. Notably, language is the best way to communicate and associate with one another both verbally and nonverbally. There is a persistent communication gap among deaf and non-deaf communities because non-deaf people have less understanding of sign languages. Every region/country has its sign language. In Pakistan, the sign language of Urdu is a visual gesture language that is being used for communication among deaf peoples. However, the dataset of Pakistan Sign Language (PSL) is not available publicly. The dataset of PSL has been generated by acquiring images of different hand configurations through a webcam. In this work, 40 images of each hand configuration with multiple orientations have been captured. In addition, we developed, an interactive android mobile application based on machine learning that minimized the communication barrier between the deaf and non-deaf communities by using the PSL dataset. The android application recognizes the Urdu alphabet from input hand configuration.

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