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     <h3 style="margin: 0; font-size: 20px;">Evaluation of mouse laryngeal inflammation upon low and high dose cigarette smoke exposures via NanoString analysis</h3>
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-      This study, conducted as part of my professional work at Stanford University, examines the effects of low- and high-dose cigarette smoke exposures on murine larynges. The research employs advanced bioinformatics methodologies, including differential gene expression analysis, functional enrichment, and network analysis, utilizing R programming and related tools. The NanoString nCounter inflammation panel is used to comprehensively evaluate inflammation and immune responses in the context of these exposures.
+      This study, conducted as part of my professional work at Stanford University, examined the effects of low- and high-dose cigarette smoke exposures on murine larynges. The research employed bioinformatics methodologies, including differential gene expression analysis, functional enrichment, and network analysis, utilizing R programming and related tools. The NanoString nCounter inflammation panel was used to comprehensively evaluate inflammation and immune responses in the context of these exposures.
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     <h3 style="margin: 0; font-size: 20px;">Calpain10 (CAPN10): Unraveling its Significance in Polycystic Ovary Syndrome (PCOS) and Insulin Resistance</h3>
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-      This academic project investigates the role of the CAPN10 gene, a key contributor to insulin resistance and Type 2 Diabetes, in the context of PCOS. Conducted as part of the UTHealth BMI 5330: Introduction to Bioinformatics course, the study integrates bioinformatics tools and databases for genome annotation, variation analysis, gene expression profiling, and functional enrichment to explore the gene's functional impact and its association with metabolic disorders.
+      This academic project investigated the role of the CAPN10 gene, a key contributor to insulin resistance and Type 2 Diabetes, in the context of PCOS. Conducted as part of the UTHealth BMI 5330: Introduction to Bioinformatics course, the project integrated bioinformatics tools and databases for genome annotation, variation analysis, gene expression profiling using R programming, and functional enrichment to explore the gene's functional impact and its association with metabolic disorders.
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