Open Access. Powered by Scholars. Published by Universities.®

Digital Commons Network™

Open Access. Powered by Scholars. Published by Universities.®

2023

Discipline
Institution
Keyword
Publication
Publication Type

Articles 241 - 244 of 244

Full-Text Articles in Entire DC Network

Identification And Characterization Of Bacteriophages For Phage Cocktail Formulation Specific To Uropathogenic Escherichia Coli, Pattida Kongsomboonchoke Jan 2023

Identification And Characterization Of Bacteriophages For Phage Cocktail Formulation Specific To Uropathogenic Escherichia Coli, Pattida Kongsomboonchoke

Chulalongkorn University Theses and Dissertations (Chula ETD)

Urinary tract infections (UTIs) are commonly found in elderlies, infants, hospitalized patients, and most women. UTIs are caused by a variety of pathogens with uropathogenic Escherichia coli (UPEC) is mostly prevalence. Even though UPEC can be treated with several antibiotics, the rapid emergence of multidrug resistant (MDR)-UPEC renders the antibiotic treatment no longer successful. Therapy using phages, which are bacterial viruses, has been considered but it is limited by bacterial resistance that develops during evolution. Fortunately, the suppression of phage resistance can be improved when used several phages as a cocktail. Here, I aim to formulate an efficient phage cocktail …

Go to article

Design, Synthesis, And Biological Evaluation Of Darunavir Analogs As Hiv-1 Protease Inhibitors, Muhammad Asad Ur Rehman Jan 2023

Design, Synthesis, And Biological Evaluation Of Darunavir Analogs As Hiv-1 Protease Inhibitors, Muhammad Asad Ur Rehman

Chulalongkorn University Theses and Dissertations (Chula ETD)

Darunavir, a potent inhibitor for HIV protease (PR) for the treatment of HIV infection, encounters limitations due to the emergence of multi-drug resistance HIV strains, imposing the development of darunavir analogs as new HIV protease inhibitors (PI) with enhanced efficacy. In this study, a combinatorial in silico method was used to at first design a several HIV-1 PI analogs with variations at key sites, P1' and P2', to improve the interactions with HIV-1 PR. Fifteen analogs with encouraging binding score were selected for synthesis and assessed for the inhibition activity of HIV-1 PR. The study demonstrated the effectiveness of P2' …

Go to article

Covidanno, Covid-19 Annotation In Human, Yuzhou Feng, Mengyuan Yang, Zhiwei Fan, Weiling Zhao, Pora Kim, Xiaobo Zhou Jan 2023

Covidanno, Covid-19 Annotation In Human, Yuzhou Feng, Mengyuan Yang, Zhiwei Fan, Weiling Zhao, Pora Kim, Xiaobo Zhou

Faculty, Staff and Student Publications

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent of coronavirus disease 19 (COVID-19), has caused a global health crisis. Despite ongoing efforts to treat patients, there is no universal prevention or cure available. One of the feasible approaches will be identifying the key genes from SARS-CoV-2-infected cells. SARS-CoV-2-infected in vitro model, allows easy control of the experimental conditions, obtaining reproducible results, and monitoring of infection progression. Currently, accumulating RNA-seq data from SARS-CoV-2 in vitro models urgently needs systematic translation and interpretation. To fill this gap, we built COVIDanno, COVID-19 annotation in humans, available at http://biomedbdc.wchscu.cn/COVIDanno/. The aim …

Go to article

3pnmf-Mkl: A Non-Negative Matrix Factorization-Based Multiple Kernel Learning Method For Multi-Modal Data Integration And Its Application To Gene Signature Detection\, Saurav Mallik, Anasua Sarkar, Sagnik Nath, Ujjwal Maulik, Supantha Das, Soumen Kumar Pati, Soumadip Ghosh, Zhongming Zhao Jan 2023

3pnmf-Mkl: A Non-Negative Matrix Factorization-Based Multiple Kernel Learning Method For Multi-Modal Data Integration And Its Application To Gene Signature Detection\, Saurav Mallik, Anasua Sarkar, Sagnik Nath, Ujjwal Maulik, Supantha Das, Soumen Kumar Pati, Soumadip Ghosh, Zhongming Zhao

Faculty, Staff and Student Publications

In this current era, biomedical big data handling is a challenging task. Interestingly, the integration of multi-modal data, followed by significant feature mining (gene signature detection), becomes a daunting task. Remembering this, here, we proposed a novel framework, namely, three-factor penalized, non-negative matrix factorization-based multiple kernel learning with soft margin hinge loss (3PNMF-MKL) for multi-modal data integration, followed by gene signature detection. In brief, limma, employing the empirical Bayes statistics, was initially applied to each individual molecular profile, and the statistically significant features were extracted, which was followed by the three-factor penalized non-negative matrix factorization method used for data/matrix fusion …

Go to article

First Prev