Mahir Yusuf Açan

About

Hi!

Hi! I'm Mahir Yusuf AÇAN. I'm 20 years old. I define myself as an ambitious student invested in improving himself in a diverse range of fields. My dream is to win the Nobel Prize in Medicine.

To briefly talk about myself, I devoted myself to Biology and Medicine and completed three papers in these fields. The first reviews MEF2A's impact on coronary disease, the second explores MAPK Targets, and the third, still in progress, uses gene expression to study P53 and CENPA in MCF10A cells. I am currently working on examining the changes in the lesion-derived region of a person with Marginal Zone Lymphoma (MZL) after BNT162b2 administration. Unfortunately, due to resource constraints, I had to put this study on hold. My future interests lie in computational biology, translational medicine, and neurogastroenterology.

I am founder of Turkish Nobel Community, and I am also a data scientist at Ultimate Premium Products(UPP).

Research

Research

Articles:

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Research Topics

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Journal

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Software

Software

Data Science

  • University Enrollment Data Model and Database: This project focuses on creating a data model and database system to effectively manage university enrollment data. It involves designing a schema, organizing student information, courses, and related data to streamline the enrollment process.
  • Analysis of Police Activities: In this project, you analyze various aspects of police activities, such as crime rates, response times, and incident patterns. By examining historical data and employing statistical techniques, you aim to gain insights into law enforcement operations and identify potential areas for improvement.
  • Analysis of the Impact of Weather on Policing: This project explores the relationship between weather conditions and policing activities. By examining weather data alongside crime data, you investigate whether certain weather conditions influence crime rates or police responses, helping to understand the impact of weather on law enforcement.
  • AutoScout: AutoScout is a data science project focused on the automotive industry. It involves analyzing vehicle data, such as prices, specifications, and features, to build a model that predicts car prices. This model can be used by individuals or businesses to estimate the value of a vehicle.
  • Cluster Analysis - Customer Segmentation: In this project, you apply cluster analysis techniques to segment customers based on their behavior, preferences, or demographics. By grouping similar customers together, businesses can tailor their marketing strategies, improve customer targeting, and enhance overall customer satisfaction.
  • E-Commerce Data and Customer Retention Analysis with SQL: Using SQL, this project involves analyzing e-commerce data to gain insights into customer behavior, purchase patterns, and factors influencing customer retention. By identifying key metrics and trends, businesses can optimize their strategies to enhance customer loyalty and improve profitability.
  • Heart Attack Analysis: This project focuses on analyzing various factors and their relationship to heart attacks. By examining medical data and employing machine learning techniques, you aim to develop predictive models that can identify individuals at risk of experiencing a heart attack, contributing to early intervention and prevention.
  • Credit Status Estimation: In this project, you use machine learning algorithms and historical credit data to estimate credit status for individuals. By analyzing various features and patterns, you aim to build a model that can assess creditworthiness, helping financial institutions make informed lending decisions.
  • NLP Emotion Analysis Project: This project involves natural language processing (NLP) techniques to analyze text data and identify the emotional sentiment expressed within it. By applying sentiment analysis algorithms, you aim to categorize texts into different emotions, such as happiness, sadness, anger, or surprise.
  • Tree Species Estimation: In this project, you use machine learning algorithms to estimate tree species based on various features like leaf shape, bark texture, and geographical location. By training a model on labeled data, you aim to develop a system that can accurately identify tree species, aiding in environmental research and conservation efforts.
  • If you wish to see the codes of this projects, you can access the public repository here.

    Blog

    Teaching

    LinkedIn:

    You can reach my blog-tye articles on this page. I have only 9 articles on this page and you can find the rest on my LinkedIn page.

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    Download CV

    Find my curriculum vitae, below. References available upon request.