WHAT DOES A BIOINFORMATICS ANALYST DO?

The Bioinformatics Analyst conducts comprehensive analyses of large-scale genomic datasets, including high-throughput sequencing, to identify genetic variants and epigenetic markers linked to specific phenotypes. This responsibility involves collaborating with development teams to refine existing tools and develop innovative AI techniques for medical applications, focusing on algorithm validation and system improvements. Additionally, the analyst will prepare data for publication, assist in its interpretation, and facilitate communication between technical and clinical research teams.

A Review of Professional Skills and Functions for Bioinformatics Analyst

1. Bioinformatics Analyst Duties

  • Data Retrieval: Use SQL and other scripting languages to retrieve relevant data from various bioinformatics databases.
  • Database Querying: Perform queries of internal LIMs and data structures.
  • Data Aggregation: Aggregate information pulled from datasets of quantitative and qualitative nature.
  • Reporting: Compile and present reports, tables, and charts to the Research and Development leads.
  • Concordance Analysis: Use Python to perform lab concordance analysis using relevant data.
  • Statistical Analysis: Use Python and/or R to perform statistical analyses on large data sets.
  • NGS Data Support: Support alignment and visualization of NGS data for troubleshooting.
  • Data Visualization: Interpret and visualize results using a variety of methods, from data aggregation to statistical analysis.
  • Collaboration: Collaborate with team members including Tempus scientists, clinicians, and BI pipeline developers.
  • Communication: Communicate findings clearly and logically to help stakeholders make scientific decisions based on data.
  • Lab Support: Support miscellaneous assay development laboratory tasks, including benchwork.

2. Bioinformatics Analyst Details

  • Data Analysis: Perform high-quality analysis of large-scale, high-throughput sequence data in combination with other genomics datasets.
  • Genetic Research: Identify mutations, genes, and epigenetic marks associated with the phenotype under study.
  • Data Interpretation: Assist in interpretation of analyzed data including the application of cutting-edge analysis methodologies and visualizations.
  • Data Preparation: Prepare analyzed data in a suitable format for dissemination.
  • Team Coordination: Serve as an intermediary between programmers and clinical/research professionals.
  • Methodology Implementation: Work with development teams to implement new methodology and tools for analysis.
  • System Improvement: Define improvements for existing systems and tools, and contribute to publications.
  • AI Development: Design, develop, and implement state-of-the-art AI techniques.
  • Algorithm Application: Reproduce and apply existing algorithms/methods/models for medical applications.
  • AI Innovation: Innovate and advance AI techniques, evaluate and improve AI algorithms/methods/models currently used.
  • AI Validation: Establish and validate algorithms/methods/models to create clinically meaningful AI tools that involve medical images.
  • Image Analysis: Assist with image data curation, processing, and analysis.

3. Bioinformatics Analyst Responsibilities

  • Data Management: Process and import relevant omics and molecular data sets, further maintain and update them for internal group use in appropriate formats.
  • Data Retrieval: Retrieve publicly available large data sets from source databases regularly and specific consortium-driven projects.
  • Data Curation: Perform data curation on the downloaded data sets according to the needs.
  • Documentation: Meticulous documentation of meta-data associated with the datasets.
  • Database Analysis: Perform various custom database queries and downstream analyses using the data mentioned above sets.
  • Data Analysis: Analyze and interpret large molecular datasets to identify targets, biomarkers, and cancer dependencies.
  • Pipeline Development: Build analyses and interpretation pipelines for omics datasets.
  • Workflow Construction: Build workflows for deploying bioinformatics tools in an HPC environment.
  • Communication: Communicate results/findings, draft and edit scientific abstracts, presentations, and journal articles.
  • Presentation: Present work at workshops, seminars, and conference proceedings within and outside of CCHMC.

4. Bioinformatics Analyst Job Summary

  • Bioinformatics Workflow: Develops, implements, and refines bioinformatic workflows and analytical tools for analyzing and visualizing NGS data.
  • Tool Adaptation: Adapts standard bioinformatics tools, visualization packages, and NGS database/annotation resources for research projects.
  • Procedure Validation: Performs validation of new procedures, protocols, software, and translational medicine projects under the direction of Bioinformatics Analyst III.
  • Database Implementation: Works with DBA and system administrator to implement and optimize databases and data storage methods.
  • Publication Contribution: Contributes to publications by providing figures, tables, and text to accurately illustrate analytical methods and results.
  • Tool Operation: Operates and troubleshoots key analytic tools and notifies the Supervisor when complex problems occur.
  • Equipment Maintenance: Operates, calibrates, maintains, and troubleshoots equipment, and notifies the Lead Clinical Analyst when complex problems occur.
  • Stakeholder Communication: Communicates effectively with technical and non-technical (internal) stakeholders.
  • Testing: Performs unit and integration testing, load-testing, and performance testing to ensure the stability and scalability of websites.
  • Technical Planning: Translates product requirements into a technical implementation plan, using skills such as OOD and analysis of existing infrastructure.
  • Project Leadership: Leads the project effort in pre-processing, processing, analyzing, and integrating the multi-omics data received from project collaborators using state-of-the-art computational and statistical approaches.

5. Bioinformatics Analyst Accountabilities

  • Project Management: Coordinate and participate in the management of research informatics implementations in a multi-disciplinary team 
  • Documentation: Develop documentation for informatics solutions by studying information needs
  • Systems Analysis: Study systems flow, data usage, regulations and institutional policies, and work processes
  • Software Development: Follow the software development lifecycle, confer with users
  • Compliance: Participate in all aspects of governance and compliance in the use of the systems, and QA reporting
  • Policy Adherence: Ensure institutional policies and procedures are adhered to and that data integrity is maintained
  • Technical Collaboration: Partner with subject matter experts, managers, and technical leads to translate business requirements to technical specifications and implementation
  • User Training: Lead and coordinate user training in REDCap and other Informatics applications
  • Project Management: Research coordinators, clinician-investigators, managers and administrators, software developers, engineers, support and reporting staff, etc.
  • User Support: Participate in continued support, troubleshooting, and services for the user community

6. Bioinformatics Analyst Functions

  • Database Management: Develop and maintain databases, and analyze and qualify data
  • Documentation: Document scripts and produce reports and presentations
  • Collaboration: Collaborate with an internal team of computational biologists, scientists, and developers to produce and maintain the database
  • Scripting: Write, test, and deploy scripts for data cleaning and database management
  • Data Acquisition: Acquire datasets from public databases as well as from internal sources
  • Data Infrastructure: Establish data infrastructure and analytics tools that meet operational and regulatory requirements
  • Planning: Collaborate with team lead, managers, and supervisors in planning, designing, implementing, and analytic reporting for all research informatics applications
  • Implementation: Participate in implementing applications using scripting or programming languages such as .Net, C#, ASPX, SQL, PL/SQL, etc.
  • Technical Documentation: Document and demonstrate solutions by developing technical and non-technical documentation, flowcharts, layouts, diagrams, and charts
  • Database Design: Design database schemas, write SQL queries, and PL/SQL procedures and packages in database systems
  • Application Management: Deploy and manage applications on a variety of application servers
  • Task Management: Provide effort estimates for tasks and track the progress of assigned tasks

7. Bioinformatics Analyst Job Description

  • Genomics Analysis: Implement, optimize, and execute computational approaches for integrative genomics analysis (RNA-Seq, Hi-C, Ribo-Seq, Lipidomics, Metabolomics), high throughput and content imaging, and kinetic analyses/modeling, cancer systems biology, development of novel algorithms and approaches.
  • Data Preparation: Use published pipelines, scripts, and tools to prepare and process large datasets.
  • Tool Development: Research, implement, test, and present new tools and pipelines for high-throughput data analysis.
  • Bioinformatics Updates: Keep informed of new developments and technical advances in bioinformatics and genomics.
  • Pipeline Design: Participate in the design and coding of analysis pipelines and cutting-edge bioinformatics analysis algorithms.
  • Presentation: Present advanced analysis results, tools, and pipelines at group meetings and contribute to publications in scientific journals.
  • Collaborative Research: Active collaborative participation in research projects with members of the Redesigning Biology Initiative.
  • Project Assistance: Contribute and assist with project inception, experimental design, analysis, and manuscript presentation.
  • Data Preparation: Assist with the preparation of data for manuscripts, publications, grant applications, posters, and other presentations.
  • Presentation: Present results verbally and with visual aids in one-on-one meetings, group meetings, or conferences.
  • Maintenance: Maintain lab notebook, including experimental design, time, methods, materials, and results.

8. Bioinformatics Analyst Overview

  • Leadership Support: Support the leadership of computational biology and systems immunology teams in performing data management, analyses, and curation tasks to support target discovery.
  • Data Acquisition: Acquire, QC, and process large-scale genomic and clinical datasets from internal groups and external collaborators.
  • Data Curation: Import, curate, and catalog public datasets to support integrative analyses of transcriptomic and clinical data towards target discovery.
  • Data Analysis: Analyze single-cell and bulk genomic datasets through established workflows.
  • Collaboration: Collaborate with computational biologists to develop and deploy custom scripts and pipelines.
  • Infrastructure Support: Aid in data analysis efforts and support computational infrastructure development.
  • Repository Maintenance: Maintain and curate internal knowledge-sharing repositories.
  • Communication: Communicate extensively with computational and experimental scientists and present results of data curation.
  • HIPAA Compliance: Work and interrogate clinical patient data adhering to HIPAA-compliant data management standards.

9. Bioinformatics Analyst Details and Accountabilities

  • Curation: Responsible for the curation and management of relevant datasets
  • Data Management: Maintain and extend a LabKey data management environment
  • Data Analysis: Data analysis and interpretation of single-cell and bulk functional genomic datasets
  • Method Development: Develop computational methods to analyze single-cell and bulk genomics datasets
  • Publishing: Publish results of scientific work in peer-reviewed journals
  • Literature Review: Keep current with knowledge in relevant scientific disciplines through continued reading of the literature
  • Conference Participation: Attend and participate in national and international scientific meetings
  • Meeting Participation: Participate in JCVI laboratory meetings and scientific working groups
  • Collaboration: Participate and present in videoconferences with project collaborators
  • Policy Adherence: Strictly adhere to all documented JCVI policies and procedures including carrying out all functions required of Institute employees

10. Bioinformatics Analyst Tasks

  • Bioinformatics: Provide bioinformatics and analytical data support to multidisciplinary departments
  • Atlas Application: Work with Atlas application and maintain knowledge of OMOP Common Data model
  • Supporting: Work with RedCap and WebCam applications to provide support to systems’ end users
  • Training: Work with key stakeholders and develop and maintain training materials for system applications
  • Documentation: Develop and maintain internal documentation such as systems requirements, designs, resource inventories, and plans
  • Testing: Perform unit, integration, and workflow testing to ensure the reliability of applications
  • Study Support: Work within the Division of Cancer Predisposition to learn and provide pipeline assistance and/or development for genetic studies in cancer predisposition
  • Reporting: Assist with the preparation of project reports, presentations, and manuscripts describing results, including a description of the approaches used to obtain these results
  • Data Management: Participate in the development of operations and procedures for the collection, editing, verification, and management of data
  • Collaboration: Work collaboratively with guidance from scientists and clinicians within the Division of Cancer Predisposition
Relevant Information
What Does A Bioinformatics Scientist Do?