Part-Time PhD Programs in Bioinformatics

Jan 01, 2020

This article explains general admission requirements and some of the common courses included in a part-time bioinformatics Ph.D. program. Continue reading to learn more details.

A Ph.D. program in bioinformatics can help students develop advanced research skills in health sciences and computational sciences to analyze biological data. Part-time programs can be more flexible and may be an advantage for working professionals; however, very few schools offer this degree with a part-time option.

Core Courses in a Part-Time Bioinformatics Ph.D. Program

In a part-time Ph.D. program in bioinformatics, students who already hold a master's degree in a related field are required to earn about 30-36 credits. You can find more details related to topics in the core courses of this program below.

Analysis of Protein Structure

Analysis of protein structure generally focuses on computer and biological methodologies for analysis, classification, and detection of protein structure. This kind of course could include different theoretical and computational techniques, approaches, tools useful for protein structure detection and analysis. Students may get a chance to learn methods like mass-spectrometry, NMR, and diffraction for detecting and determining the protein structure. Evaluation of modifications, their importance in metabolism and diseases, and different methods for predicting modifications could also be a part of this course.

Biological Data Analysis and Mining

In biological data analysis and mining, students may learn different research methodologies and tools for biological data analysis. Data collection techniques, different mining concepts for large data sets of life-sciences, algorithms to discover patterns in the collected data, and making predictions based on these patterns could be a part of this sort of course. Students may explore various data mining toolsets such as the Weka toolkit. This course could include research examples and case studies to explain the practical approach of this study.

Computational Methods for Bioinformatics

Computational methods for bioinformatics typically introduces different computational techniques and tools in bioinformatics to solve biological problems in a scientific approach. This kind of course may also include dynamic programming concepts to help students in writing an efficient computer program to solve quantitative biological problems. Bioinformatics methodologies such as bio-sequence analysis, hidden Markov models, phylogenetic trees, and genome sequencing and assembly could be a part of this course, as well.

Systems Biology Concepts

In coursework related to systems biology concepts, students can explore different experimental techniques and concepts related to genomics, transcriptomics, proteomics, and network data analysis. This type of course often enables students to explore biological systems with a detailed study of omics data. Students may also take a look at the functioning of a complex biological system by using different computational methods and algorithms. Hands-on exercises and case studies could be a part of this course for a practical understanding of these concepts.

Admission Requirements

Applicants might need to hold a bachelor's degree from an accredited school in computer science, biology, statistics, or other related disciplines with a cumulative GPA of 3.0 to 4.0. Students might also need to show good quantitative scores in the GRE to get admissions into this Ph.D. program. Additionally, a resume, official transcript from previous schools, letters of recommendation, and a personal statement explaining professional and academic achievements could be necessary.

In a part-time Ph.D. program in bioinformatics, students can learn several methodologies and tools useful to design computational systems for biological data analysis and predictions in health sciences. The schools typically expect applicants to hold a bachelor's degree with a GPA of 3.0 to 4.0 to be eligible for the admissions process.

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