A master's degree in bioinformatics includes study in biology and computer science, and it also gives students tools to analyze medical data in an advanced computational environment. Different schools across the U.S. offer this program in a part-time format with the same coursework as a full-time program.
Part-Time Bioinformatics Master's Programs
Bioinformatics master's programs may require up to 36 credit hours and two years of study; those studying part time can often take up to five years to complete the program. In addition to theoretical classes related to biology and computer science, programs can include different hands-on projects, internships, and research projects to understand real-world working. The curriculum typically consists of some of the common course subjects listed below.
Statistics Concepts for Bioinformatics
This kind of course focuses on teaching statistics methods for the analysis of medical data. It might include advanced topics such as probability, univariate and multivariate techniques, and regression analysis. It might also include different software tools and packages used for statistical analysis. R programming might be a part of this course to analyze complex datasets and provide hands-on programming experience for designing solutions to analyze the datasets.
Computational Algorithms for Bioinformatics
In this type of course, students can explore various computer algorithms, mathematical methods, and tools to perform analysis of biological data. Students can learn to choose a suitable method for problem analysis, understanding the similarity between existing problems and new problems. Students can also learn to design efficient methods for analysis, adopting methods designed for current challenges to new challenges, and evaluating computational methods for performance and accuracy.
Generally, in this course, students focus on different web-based tools, query languages, and software packages to manage and secure a database. This kind of course typically includes relational database concepts, query language like SQL, ORACLE database management concepts, and relational algebra with emphasis on storing the biological data based on structure, genetic linkages, or other sequences. By the end of this course, students can also learn advanced database concepts such as data indexing and query optimization techniques.
Next-Generation Sequence Analysis Concepts
This course may provide the best practices for modern sequencing, computational and statistical methods, sequencing platforms, various data formats, and sequence alignment in detail. It might also focus on teaching the advantages and limitations of popular bioinformatics analysis methods. It could also include different sequencing approaches, such as genome and exome. Students can get an opportunity to analyze real-world data in advanced computational environments.
Fundamentals of Proteomics
This type of course typically explores the concepts of separation and structure of protein molecules. Experimental techniques such as mass spectrometry, chromatography, X-ray, 2D gel electrophoresis, and NMR might be a part of this course. Efficient bioinformatics approaches, usage of software tools, and implementing algorithms for the prediction of protein structure could be a part of this course. Students may participate in hands-on programs to understand various experimental methods.
A baccalaureate degree in computers, biology, chemistry, biotechnology, mathematics, or a related field might be required to be eligible for this program. In some schools, applicants with no science or technical background might need to complete preparatory coursework in relevant topics. Some other schools prefer candidates with a minimum GPA of 3.2 in undergraduate studies. Additionally, students might need to submit a personal statement, resume, official transcripts from previous schools, and two to three recommendation letters along with an online application.
In a part-time master's program in bioinformatics, students can learn different statistical, mathematical, and computational methods to analyze biological and medical data, and they can get an opportunity to perform experimental work for hands-on practice. A bachelor's degree with a relevant background might be necessary to pursue this program.