Syed Asif Ali*, Neelam and Izna Waseem
DOI: 10.37421/0974-7230.2023.16.492
In this paper, we will refer to hereditary hearing loss. Hearing loss is a genetic as well as accidental problem. Genetic deafness is a type of hearing loss that is caused by changes or mutations in genes related to the hearing process. These mutations can be inherited from one or both parents and can occur spontaneously. There are two types of genetic deafness: Syndromic and non-syndromic. The inheritance of genetic deafness depends on the type of mutation and the pattern of inheritance. Some mutations are dominant, other mutations are recessive, X-linked inheritance is another type of inheritance, and mitochondrial inheritance which are described in detail in our paper. Some authors have suggested that rather than publicly condemning deaf parents that choose deafness for their children, we believe that this technique can be viewed as unacceptable. In today's technological world it is needed to construct and design models related to certain topics and automate it. The idea of how to create an automata model with some techniques is described in this paper. But deaf people are still considered less capable as compared to normal humans, which do not help in the betterment of the society but rather to select genetic factors that are typically seen as a handicap by majority of the sociological environment. The inheritance of genetic deafness follows the rules of Mendelian genetics, where the genes are passed down from parents to their offspring.
Alireza Khanteymoori1*, Soudeh Behrouzinia1 and Fariba Dehghanian2
Inspired by biological systems and grounded in mathematical and computational models, complex networks have been extensively employed to represent diverse biological phenomena. The significance of network controllability in comprehending intricate biological systems is universally acknowledged, leading to the development of several algorithms aimed at analyzing network controllability. These algorithms serve the purpose of manipulating input signals to guide biological system dynamics toward desired states. New studies in biological systems have shown that there are complicated connections between nodes that are hard to show in simple networks. In response to these complexities, multiplex networks have emerged as robust constructs capable of accommodating and capturing multiple relationships simultaneously simultaneously within high-dimensional spaces. This research introduces a framework designed to regulate the behavior of biological multiplex networks by identifying pivotal driver nodes. This framework is presented to identify minimum driver nodes that the efficacy of it evaluated through its application to authentic biological multiplexes. Applied to three virus multiplex networks, the framework underscores the potential for identified driver nodes to serve as targets for drug enrichment or as subjects for investigating intricate diseases. The implications of this research extend to identifying potential driver genes for various virus-related diseases within the landscape of biological multiplex networks.
Osama Y Abu Tammam
The paper introduces Monte Carlo Area Algorithm using Mat lab simulation to generate uniform random distribution points and evaluate the area accordingly and analyze the error. The method to calculate the error had done by comparing the real area value and estimated area values the repetition of the algorithm introduce superior efficiency and reduce the difference between real area value and estimated which considered as error. The relation between Error and number of random points is obviously an exponential relation which affected by number of repetition and random points. The true challenge in such studies is to limit the deviation in the exponential relation between error and number of random points.
Moses Orimoloye Akinjiyan*, Olusola Olalekan Elekofehinti, Ayomide Precious Ajiboro, Elizabeth Foluke Awodire, Adeodotun Olayemi Oluwatuyi and Stephen Adeleke Adesida
DOI: 10.37421/0974-7230.2022.15.432
Erectile Dysfunction (ED) has been a threat among couples and is one of the challenging disorders in Nigeria and the world. Various drugs targeting Phosphodiesterase 5 (PDE5) inhibition like Pyrazinopyridoindole (Tadalafil), have been used for the treatment of ED but, they are associated with side effects such as headache, diarrhea, back pain, and stomach upset among others. Medicinal plants are now being explored for the treatment of various diseases and disorders including ED because they are affordable with little or no side effects. Cissus populnea (CP) is a popular plant in Nigeria used in the management of ED but there is a paucity of information on the mechanisms involved. In this study, Schrodinger suites were employed for docking of thirty-eight CP phytocompounds gotten from HPLC analysis and works of literature against Phosphodiesterase PDE5, a key enzyme in the erection pathway. Seven leading compounds were found to have higher docking scores and binding affinity compared to Pyrazinopyridoindole (Tadalafil), with 9-octadecenoic acid, having the highest docking score of -13.078 Kcal/mol. The hit compounds were further subjected to ADME prediction. The findings suggested that C. populnea compounds are potential drug candidates with better hit than Tadalafil in managing ED and merit additional investigation.
DOI: 10.37421/0974-7230.2023.16.452
Smaranya Dey, Subhadip Paul, Uddipto Dutta and Anirban Chatterjee
Mahboobeh Zohourian, Marzieh Shekari, Hossein Zamani and Moftakhar Ahmadi
Journal of Computer Science & Systems Biology received 2279 citations as per Google Scholar report
Spanish 
Chinese 
Russian 
German 
French 
Japanese 
Portuguese 
Hindi 