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  1. Programs
  3. Bioinformatics - BS

Bioinformatics - BS

Texas A & M University-College Station

Bachelor's DegreeAcademic

Become a contributor for free to openly demonstrate student outcomes, industry alignment & eligibility criteria.

The Bioinformatics curriculum focuses on cultivating students with knowledge and expertise in biology, statistics, computer science, and, most importantly, the seamless integration of these diverse domains.

Credits

120 credits

Format

In-Person

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Program Pathways

Credentials this program stacks toward

No program pathways.

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Program Details

Detailed information about this program

No detailed information available.

Requirements

What you need to earn this credential

No requirements listed.

Financial Aid

Eligible funding programs

No funding information available.

Scholarships

No scholarships listed.

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Locations

Where this program is offered

  • Texas

    Texas

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Related Programs

Programs related to this one

No related programs.

Skills & Competencies

Skills developed through this program

Auto-populated·from O*NET via SOC 19-1029.01

Skills

Reading ComprehensionCritical ThinkingComplex Problem SolvingActive ListeningSpeakingWritingScienceJudgment and Decision Making

Knowledge

BiologyComputers and ElectronicsMathematicsEnglish LanguageChemistry

Abilities

Written ComprehensionWritten ExpressionOral ComprehensionOral ExpressionProblem SensitivityDeductive ReasoningInductive ReasoningInformation OrderingFluency of IdeasMathematical Reasoning

Tasks

  • Develop new software applications or customize existing applications to meet specific scientific pro
  • Communicate research results through conference presentations, scientific publications, or project r
  • Create novel computational approaches and analytical tools as required by research goals.

Technology

Analytical or scientific softwareData base user interface and query softwareObject or component oriented development softwareData base management system softwarePortal server software

Tools

Computer data input scannersComputer laser printersDesktop computersLaptop computersPersonal computers

Work Values

IndependenceAchievementRecognitionWorking ConditionsSupportRelationships
Career Pathways

Occupations this program prepares you for

Auto-populated·from O*NET + BLS
Occupations matched to this program, with median wage, top wage, growth, and openings
SOCOccupationMethodWageGrowthOpenings
Match confidence: medium19-1029.01Bioinformatics Scientiststitle_inference———
What You'll Learn

Key competencies developed through this program

Auto-populated·from NSX Competency Framework

Mastery: proficient (Level 3)(based on Bachelor's Degree)

  • Novel computational algorithms for sequence analysis or structural prediction — design, implement, and benchmark autonomously to address research goals that exceed the capability of existing published tools.
  • Complex multi-omics datasets spanning genomics, transcriptomics, and proteomics — integrate and interpret across full analytical scope to generate actionable biological insights for clinical or translational research programs.
  • Custom bioinformatics applications — architect and develop end-to-end using object-oriented or functional programming frameworks, deploying on cloud or HPC infrastructure with robust documentation and version control.
  • Interdisciplinary research teams including wet-lab scientists, clinicians, and computational staff — consult with autonomously to diagnose analytical problems, evaluate technology-based solutions, and guide study design decisions.
  • Peer-reviewed scientific publications and conference presentations — author and deliver as lead or corresponding scientist, translating complex computational findings for broad life-science audiences.
  • Multi-terabyte genomic databases and data warehouses — design, optimize, and govern using advanced DBMS and portal server technologies to support institution-wide research data needs.
  • Emerging biochemical assays and bioinformatics software releases — critically evaluate for methodological rigor, rapidly adapt laboratory workflows, and mentor junior staff on adoption strategies.
  • Analytical or scientific software platforms — customize and extend through API integration and enterprise application integration tools to meet highly specific and non-routine research requirements.
  • Systems-level evaluation of computational pipelines — perform to assess performance, reproducibility, and biological validity across diverse datasets and experimental conditions in a high-stakes research environment.
  • Mathematical modeling and statistical inference frameworks — apply with full autonomy to develop quantitative hypotheses and validate predictions against experimental molecular biology data.

Some details on this page are auto-populated from public workforce data sources: O*NET (opens in new tab), BLS (opens in new tab), College Scorecard (opens in new tab), DOL Training Provider Results (opens in new tab), NSX (opens in new tab). Provided in partnership with LER.me Career Intelligence.

Student Outcomes

Performance metrics for this program

Completion Rate
Not reported
Placement Rate
Not reported