Computer Science BS Bioinformatics

Program Purpose


The Bioinformatics Emphasis has the same Purposes and learning outcomes as the traditional Computer Science Major. Additionally, students gain the biological background that enables them to create applications that solve significant problems in computational biology.  Graduates in Computer Science are prepared to be competent software developers and technical problem solvers. Students are also prepared for research into new avenues where computers will have a significant impact, and a large number of our graduates pursue graduate degrees in Computer Science or other disciplines. Graduates are prepared for the lifelong learning necessary in this fast-moving field, including a solid background in both rigorous theoretical foundations and practical training.

Curricular Structure

Students have shown interest in this emphasis as a way to prepare them for employment as software developers in this growing area. This emphasis will also allow pre-med and pre-dental students to fulfill the requirements of these programs along with computer science in a more reasonable amount of time. Some pre-law students have expressed an interest in this degree program as they view the large body of patent law that will be decided in the next few years as this new technology becomes more mainstream. The Bioinformatics Emphasis represents several areas where the Department of Computer Science is solving exciting problems using computers.

In addition to the required core, students take five senior-level elective courses to help them tailor their curriculum to their individual interests. Students gain experience in working with biological data in Bio 365 and Bio 465.  In these classes they are able to apply the theoretical and practical skills they gained in the biology and Computer Science courses..

The faculty members in the department have a broad background of both industrial and academic experience. They share a wide range of interests with the students in both the undergraduate and graduate classes and in their research laboratories.

For more information, see the program's Catalog Description

Major Academic Plan (MAP)

 

 

Learning Outcomes


Computational Practice

Students will design and implement significant computer programs that meet a human need and will develop expertise in bioinformatics. See the Computer Science BS program for general assessments shared across all emphases.

Courses that Contribute: BIO 365 BIO 465 BIO 130 BIO 463 C S 142 C S 235 C S 236 C S 240 C S 312 C S 340 C S 345 C S 401R C S 428 C S 431 C S 450 C S 452 C S 455 C S 456 C S 460 C S 462 C S 465 C S 470 C S 478 C S 479 C S 484 MMBIO 240
Linked to BYU Aims: Think soundly, Human knowledge, Competence
Computational and Biological Theory

Students will analyze problems and their algorithmic solutions using theoretical concepts from computer science and biology. See the Computer Science BS program for general assessments shared across all emphases.

Courses that Contribute: BIO 130 BIO 463 C S 235 C S 236 C S 240 C S 252 C S 312 C S 340 C S 345 C S 431 C S 450 C S 452 C S 460 C S 479 MATH 112 MMBIO 240
Linked to BYU Aims: Think soundly, Quantitative reasoning, Human knowledge, Competence
Career Preparation

Students will have sufficient maturity in computer science to work in a professional setting in computer science or bioinformatics or to enter a graduate program. See the Computer Science BS program for general assessments shared across all emphases.

 

 

Courses that Contribute: BIO 130
Linked to BYU Aims: Lifelong learning, Lifelong service
Diversity, Equity, and Inclusion

Our program is accessible to everyone, including women, minorities, and those new to programming, and provides an equal opportunity for every student to succeed. See the Computer Science BS program for general assessments shared across all emphases.

 

Courses that Contribute: None
Linked to BYU Aims: Faith and testimony, Character

Evidence of Learning


The Computer Science Department is developing several mechanisms over the next several years (2020 - 2021) that will measure the competency of graduating students. Please see the Computer Science BS program for direct and indirect measures relevant to all Computer Science programs. Below are additional measures specific to this emphasis.

Direct Measures

  1. Computational Practice
    • A locally developed Field Assessment that will evaluate competency for both computational practice and computational theory. Questions in relevant classes will evaluate computational practice specific to this emphasis. 
  2. Computational Theory
    • A locally developed Field Assessment, as described above.
  3. Career Preparation
    • Measurements of student placement in jobs and graduate school, including the percentage having a job offer in the emphasis field and separately the percentage having a job offer in another computer science field.

Performance Criteria

The following performance criteria are used to assess performance on the direct measurements that are specific to this emphasis:

Computational Practice

  1. Field Assessment, Emphasis subset. Outstanding: 90% and above, Acceptable: 80-89%, Marginal: 60-79%, Unacceptable: 59% and below.

Computational Theory

  1. Field Assessment, Emphasis subset. Outstanding: 90% and above, Acceptable: 80-89%, Marginal: 60-79%, Unacceptable: 59% and below.

Career Preparation

  1. Percentage of students having a full time job in computer science 6 months after graduation. Of this, which percentage have a job in the emphasis field. Outstanding: 90% and above, Acceptable: 80-89%, Marginal: 60-79%,Unacceptable: 59% and below. Emphasis jobs: 60%

     

Learning and Teaching Assessment and Improvement


Please see the Computer Science BS program for the assessment and improvement plan. For emphases, the undergraduate committee will work with faculty who oversee those emphases to review data and make plans for improvement.