Student Research Symposium Program Portal: Submission #207

serial: '207'
sid: '9055'
uuid: ef93c6d6-f557-477a-85c2-07b0941c0278
uri: /student-research/symposium/research-symposium-program-portal
created: '1769784868'
completed: '1769784932'
changed: '1769784932'
in_draft: '0'
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remote_addr: 146.201.10.32
uid: '0'
langcode: en
webform_id: research_portal
entity_type: node
entity_id: '14501'
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notes: ''
metatag: meta
data:
  abstract: "The p53 protein, or the “guardian of the genome,” is one of the body's biggest natural defenses against cancer. Therefore, understanding this protein could lead to big improvements in cancer research. But P53 is an incredibly dynamic protein, constantly moving and changing into different conformational states, because of this its extremely hard to model with traditional methods. Modeling the P53 protein using machine learning technology could be the thing to get accurate and insightful models. To research whether machine learning could create more accurate models than traditional methods, I will utilize AlphaFold to generate multiple models of the p53 protein and compare them to p53 models created using traditional methods that are found online in large databases such as ChimerX. If the models are as accurate or more accurate than traditional models, then I will use AlphaFold to create rarer conformational states of p53 and compare them to rare models created using traditional methods. If these models are as accurate or more accurate than traditional ones, I will finally attempt to create extremely rare or unknown conformational states. The real world significance of my research is not only a huge leap in cancer research but also a huge leap in complex protein modeling, which has a significant number of applications in many different fields."
  additional_research_mentor: ''
  annual_description: '5th annual Undergraduate Research Symposium, April 17, 2025'
  co_presenters: ''
  first_name: Zachariah
  i_will_be_printing_my_poster: '0'
  keywords: 'Machine learning, Micro biology, protein modeling '
  last_name: Zawahry
  major: 'intended major biology'
  poster_pdf: ''
  poster_session_number: ''
  poster_thumbnail: ''
  presentation_modality: 'Face to Face Poster session'
  pronouns: ''
  research_mentor: 'Madyson Flamia'
  research_mentor_s_college: 'FSU Collegiate School'
  research_mentor_s_department: 'Research departmant'
  research_mentor_s_email: mjf24@fsu.edu
  student_bio: 'I am a dual-enrolled student at the FSU collegiate school. I was born and raised in Panama City, Florida. I volunteer for multiple organizations, such as AMAL and Florida Springs Watch, as well as play varsity soccer for Bay High School. I am deeply intrigued by microbiology and plan to go into the medical field.'
  student_email: zz23f@fsu.edu
  student_photo: '72895'
  title: 'Machine learning in respect to P53 protien'
  update_url: 'https://pc.fsu.edu/student-research/symposium/research-symposium-program-portal?element_parents=elements/student_photo&ajax_form=1&_wrapper_format=drupal_ajax&token=w4WZjkT7KN-w2dmOJJpe2thTjlQv8a9MmYMOYm4mBdk'
  work: Exploratory
  year: '2026'