Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Syed Mudasir Andrabi"'
Autor:
Syed Douhath Yousuf, Mohammad Ashraf Ganie, Uneeb Urwat, Syed Mudasir Andrabi, Mohammad Afzal Zargar, Mashooq Ahmad Dar, Mir Manzoor-ul-Rehman, Syed Mudassar, Fouzia Rashid
Publikováno v:
BMC Women's Health, Vol 23, Iss 1, Pp 1-15 (2023)
Abstract Background Polycystic ovary syndrome (PCOS) presents clinical symptoms of menstrual abnormalities, excessive hair growth (hirsutism), scalp hair loss, acne and infertility. Metabolic abnormalities such as obesity, insulin resistance, glucose
Externí odkaz:
https://doaj.org/article/a0700457af504b9f8001cc445fa328dd
Long non-coding RNAs (LncRNAs) were originally regarded as “noise” in the genome due to their lack of protein-encoding capacity. However, their roles are now understood to cover various biological functions like gene regulation, cell proliferatio
Autor:
Khalid Z. Masoodi, Nazeer Ahmed, Mudasir A. Mir, Basharat Bhat, Afshana Shafi, Sheikh Mansoor, Rovidha S. Rasool, Mifftha Yaseen, Zahoor A. Dar, Javid I. Mir, Syed Mudasir Andrabi, Nazir A. Ganai
Publikováno v:
Functional & Integrative Genomics. 22:1315-1330
Androgen receptor signalling transactivator lncRNAs PRNCR1 and PCGEM contribute to PCOS pathogenesis
polycystic ovary syndrome is the most common endocrine, reproductive disorder of women in their reproductive years. It is commonly considered as an androgenic disorder. Apart from high circulating testosterone levels, hyperandrogenism can also be att
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7d2e710a2e5921cf7cd69669c8af5db
https://doi.org/10.21203/rs.3.rs-2598360/v1
https://doi.org/10.21203/rs.3.rs-2598360/v1
Autor:
Ambreen Hamadani, Nazir A Ganai, Syed Mudasir Andrabi, Syed Shanaz, Safeer Alam, Ishraq HussainSher-e-Kashmir
As the amount of data on farms grows, it is important to evaluate the potential of artificial intelligence for making farming predictions. Considering all this, this study was undertaken to evaluate various machine learning (ML) algorithms using 52-y
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::598d528ab6d34bfafb4d1db2dc91b396
https://doi.org/10.21203/rs.3.rs-1488946/v1
https://doi.org/10.21203/rs.3.rs-1488946/v1
Autor:
Qamar Taban, Basharat Bhat, Shakil Ahmad Bhat, Mashooq Ahmad Dar, Dinesh Velayutham, Riaz Ahmad Shah, Nadeem Shabir, Syed Mudasir Andrabi, Zulfkar ul Haq, Peerzada Tajamul Mumtaz, Mengqi Wang, Eveline M. Ibeagha-Awemu, Nazir Ahmad Ganie
Publikováno v:
BMC Genomics. 23
Background Long noncoding RNAs (lncRNAs) are now proven as essential regulatory elements, playing diverse role in many biological processes including mammary gland development. However, little is known about their roles in bovine lactation process. T
Autor:
Nissar A. Bhat, Zaffar Iqbal, Saima S. Mir, Basharat A. Bhat, Aadil Ayaz, Zuhaib F. Bhat, Riaz A. Shah, Nazir A. Ganai, Syed Mudasir Andrabi, Hina F. Bhat
Publikováno v:
Indian Journal of Animal Research.
Background: Keratin-associated protein’s (KRTAPs) are the major constituent proteins of cashmere fibre and have been implicated to have an important effect on the quality traits of this commercially valuable fibre. The objective of the present stud
Autor:
Ambreen Hamadani, Nazir A. Ganai, Tariq Raja, Safeer Alam, Syed Mudasir Andrabi, Ishraq Hussain, Haider Ali Ahmad
Publikováno v:
Bhartiya Krishi Anusandhan Patrika.
Background: Sheep farm data is often biased by extreme values which are generally introduced due to errors in manual measurement. These values interfere with the accuracy of estimations especially in state-of-the-art techniques like Machine Learning.
Autor:
Mudasar Nabi, Shajrul Amin, Syed Mudasir Andrabi, Imran Majid, Sairish Ashraf, Shayaq Ul Abeer Rasool
Objective: Polycystic ovary syndrome (PCOS) is one of the most common reproductive, endocrine and metabolic disorders in premenopausal women. Even though the pathophysiology of PCOS is complex and obscure, the disorder is prominently considered as th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9055a67680965eeaa9e8451b5baec735
https://doi.org/10.21203/rs.3.rs-633719/v1
https://doi.org/10.21203/rs.3.rs-633719/v1