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  1. Programs
  3. Bioinformatics for Rare Diseases

Bioinformatics for Rare Diseases

National Institutes of Health (NIH)

Micro-CredentialCIP: 26.1105

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

A course focused on bioinformatics approaches to understand and diagnose rare genetic disorders using genomic data.

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Program Pathways

Credentials this program stacks toward

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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

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Locations

Where this program is offered

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Related Programs

Programs related to this one

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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: emerging (Level 1)(based on Micro-Credential)

  • Molecular datasets from genomic sequencing runs — process and quality-filter using established bioinformatics pipelines under close faculty or senior scientist supervision.
  • Existing bioinformatics software tools — install, configure, and execute on a university HPC cluster following documented protocols and lab-specific workflows.
  • Scientific literature on emerging biochemistries and sequencing technologies — read, summarize, and present key findings at weekly lab journal-club meetings.
  • Relational databases for biological data storage — populate and query using standard SQL commands under guidance from a senior bioinformatician.
  • Raw microarray or RNA-seq expression data — compile and format into analysis-ready matrices by applying prescribed preprocessing scripts in a supervised research environment.
  • Object-oriented programming languages such as Python or R — write basic scripts to automate repetitive data-formatting tasks within an established laboratory codebase.
  • Research findings and preliminary analyses — document clearly in internal project reports following laboratory style guidelines and under mentor review.
  • Computational strategies proposed by research collaborators — assist in evaluating feasibility by reviewing relevant literature and running benchmark tests under direction.
  • Genome annotation reference files and public biological databases — retrieve, cross-reference, and organize for use in ongoing research projects under senior oversight.
  • Mathematical and statistical concepts underlying sequence alignment or differential expression — apply foundational methods correctly when executing standard analytical workflows in a research lab setting.

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