Bioinformatics and Computational Biology Bachelor of Science Degree

In this dynamic bioinformatics BS, biology and computing combine to analyze big data collected by the health industry to discover, diagnose, and treat a wide range of medical conditions.


4+1

5-year BS/MS in Bioinformatics

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Equipment in Genomics Lab


Overview for Bioinformatics and Computational Biology BS

Why Study Bioinformatics at RIT?

  • Gain Hands-on Experience: Sequence and annotate whole genomes of a variety of organisms using the Illumina MiSeq in the Genomics Lab.
  • Industry Work Experience: Bioinformatics students gain career exposure and hands-on experience through a required co-op experience.
  • Jobs at Industry Leading Companies: Recent bioinformatics graduates are employed at the Cleveland Clinic, Newport Labs, and the Dana-Farber Cancer Institute.
  • A 100% Outcomes Rate: Bioinformatics graduates jump into a number of exciting careers immediately after graduation. They utilize their analytical and computational skills to solve real-world problems.

Bioinformatics is the intersection of biology and computer science. When enrolled in RIT’s bioinformatics bachelor's degree, you’ll learn how to use computers to analyze, organize, and visualize biological data in ways that increase the understanding of this data and lead to new discoveries.

RIT’s Bioinformatics and Computational Biology Bachelor of Science Degree

The RIT bioinformatics BS includes laboratory exercises and assignments in which you’ll learn to sequence DNA and use computer programs to analyze DNA sequences and predict molecular models. You will also gain critical skills employers look for, including:

  • Fundamental training/knowledge in molecular biology, biochemistry and biotechnology, particularly genomics and relational database administration
  • Programming skills, such as the ability to use SQL, PERL, C, C++, etc. on a UNIX operating system
  • Strong analytical abilities using relevant mathematical/statistical tools
  • A strong interest in utilizing computational skills to leverage the data outcomes of those working in the laboratory
  • The ability to multitask and meticulously perform the same task repetitively, while working independently

Bioinformatics Careers

Bioinformatics has become essential to the biological sciences. In the past, laboratories were able to manage and analyze their experimental data in spreadsheets. Many research labs now require the expertise of dedicated bioinformatics core centers or their own in-house bioinformaticists. Our bioinformatics and computational biology BS graduates have entered such laboratories, both in industry and academia, as bioinformaticists. Some have also leveraged their biotechnology experiences as wet lab experimentalists themselves. The diversity of skills our students cultivate has given them access to a wide range of career choices.

Furthering Your Education in Bioinformatics

Combined Accelerated Bachelor’s/Master’s Degrees

Today’s careers require advanced degrees grounded in real-world experience. RIT’s Combined Accelerated Bachelor’s/Master’s Degrees enable you to earn both a bachelor’s and a master’s degree in as little as five years of study, all while gaining the valuable hands-on experience that comes from co-ops, internships, research, study abroad, and more.

  • +1 MBA: Students who enroll in a qualifying undergraduate degree have the opportunity to add an MBA to their bachelor’s degree after their first year of study, depending on their program. Learn how the +1 MBA can accelerate your learning and position you for success.
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Careers and Experiential Learning

Typical Job Titles

Bioinformatics Analyst Biomedical Researcher
Biostatistician Computational Biologist
Geneticist Research Technician
Laboratory Technician Software Programmer
Technical Support Specialist

Industries

  • Biotech and Life Sciences
  • Medical Devices
  • Pharmaceuticals
  • Health Care

Cooperative Education

What’s different about an RIT education? It’s the career experience you gain by completing cooperative education and internships with top companies in every single industry. You’ll earn more than a degree. You’ll gain real-world career experience that sets you apart. It’s exposure–early and often–to a variety of professional work environments, career paths, and industries. 

Co-ops and internships take your knowledge and turn it into know-how. Science co-ops include a range of hands-on experiences, from co-ops and internships and work in labs to undergraduate research and clinical experience in health care settings. These opportunities provide the hands-on experience that enables you to apply your scientific, math, and health care knowledge in professional settings while you make valuable connections between classwork and real-world applications.

Students in the bioinformatics and computational biology degree are required to complete one cooperative education experience.

National Labs Career Events and Recruiting

The Office of Career Services and Cooperative Education offers National Labs and federally-funded Research Centers from all research areas and sponsoring agencies a variety of options to connect with and recruit students. Students connect with employer partners to gather information on their laboratories and explore co-op, internship, research, and full-time opportunities.  These national labs focus on scientific discovery, clean energy development, national security, technology advancements, and more. Recruiting events include our university-wide Fall Career Fair, on-campus and virtual interviews, information sessions, 1:1 networking with lab representatives, and a National Labs Resume Book available to all labs.

Featured Work

Featured Profiles

Curriculum for 2023-2024 for Bioinformatics and Computational Biology BS

Current Students: See Curriculum Requirements

Bioinformatics and Computational Biology, BS degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
BIOL-123
Introduction to Biology: Organisms and Ecosystems (General Education)
This course serves as an introduction to biology for majors, focusing on the organismal, population, and ecosystem levels. Major themes include: evolution, structure and function, information flow and storage, pathways and transformations of energy and matter, and systems. The course also focuses on developing core competencies, such as applying the process of science, using quantitative reasoning, communicating, and collaborating. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.) Lecture 3 (Fall).
3
BIOL-124
Introduction to Biology: Molecules and Cells (General Education)
This course serves as an introduction to biology for majors, focusing on the molecular and cellular level. Major themes include: evolution, structure and function, information flow and storage, pathways and transformations of energy and matter, and systems. The course also focuses on developing core competencies, such as applying the process of science, using quantitative reasoning, communicating, and collaborating. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.) Lecture 3 (Spring).
3
BIOL-125
Introduction to Biology Laboratory: Organisms and Ecosystems (General Education)
This course is an introduction to laboratory work in life sciences. The laboratory work is project-based, and may involve field work as well as laboratory experiments. The course is designed to show the huge scope of biology and will encompass how some molecular biology and bioinformatics techniques connect with organismal and ecological biology. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students. Co-requisites: BIOL-123 or equivalent course.) Lab 3 (Fall).
1
BIOL-126
Introduction to Biology Laboratory: Molecules and Cells (General Education)
This course is an introduction to laboratory work in life sciences. The laboratory work is project based, and the subject matter of the project(s) may vary. The course is designed to show the huge scope of biology and will encompass some molecular biology and bioinformatics techniques connect with organismal and ecological biology. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students. Co-requisites: BIOL-124 or equivalent course.) Lab 3 (Spring).
1
BIOL-130
Introduction to Bioinformatics
This course will explore topics in the field of bioinformatics including tools and resources used by the discipline, including direct experience with the common user environment. Lecture 3 (Fall).
3
CHMG-141
General & Analytical Chemistry I (General Education – Natural Science Inquiry Perspective)
This is a general chemistry course for students in the life and physical sciences. College chemistry is presented as a science based on empirical evidence that is placed into the context of conceptual, visual, and mathematical models. Students will learn the concepts, symbolism, and fundamental tools of chemistry necessary to carry on a discourse in the language of chemistry. Emphasis will be placed on the relationship between atomic structure, chemical bonds, and the transformation of these bonds through chemical reactions. The fundamentals of organic chemistry are introduced throughout the course to emphasize the connection between chemistry and the other sciences. Lecture 3 (Fall, Spring, Summer).
3
CHMG-142
General & Analytical Chemistry II (General Education – Scientific Principles Perspective)
The course covers the thermodynamics and kinetics of chemical reactions. The relationship between energy and entropy change as the driving force of chemical processes is emphasized through the study of aqueous solutions. Specifically, the course takes a quantitative look at: 1) solubility equilibrium, 2) acid-base equilibrium, 3) oxidation-reduction reactions and 4) chemical kinetics. (Prerequisites: CHMG-141 or CHMG-131 or equivalent course.) Lecture 3 (Fall, Spring, Summer).
3
CHMG-145
General & Analytical Chemistry I Lab (General Education – Natural Science Inquiry Perspective)
The course combines hands-on laboratory exercises with workshop-style problem sessions to complement the CHMG-141 lecture material. The course emphasizes laboratory techniques and data analysis skills. Topics include: gravimetric, volumetric, thermal, titration and spectrophotometric analyses, and the use of these techniques to analyze chemical reactions. (Corequisite: CHMG-141 or CHMG-131 or equivalent course.) Lab 3 (Fall, Spring, Summer).
1
CHMG-146
General & Analytical Chemistry II Lab (General Education)
The course combines hands-on laboratory exercises with workshop-style problem sessions to complement the CHMG-142 lecture material. The course emphasizes the use of experiments as a tool for chemical analysis and the reporting of results in formal lab reports. Topics include the quantitative analysis of a multicomponent mixture using complexation and double endpoint titration, pH measurement, buffers and pH indicators, the kinetic study of a redox reaction, and the electrochemical analysis of oxidation reduction reactions. (Prerequisites: CHMG-131 or CHMG-141 or equivalent course. Corequisites: CHMG-142 or equivalent course.) Lab 3 (Fall, Spring, Summer).
1
MATH-181
Calculus I (General Education – Mathematical Perspective A)
This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH-111 or (NMTH-220 and NMTH-260 or NMTH-272 or NMTH-275) or equivalent courses with a minimum grade of B-, or a score of at least 60% on the RIT Mathematics Placement Exam. Co-requisites: MATH-181R or equivalent course.) Lecture 6 (Fall, Spring).
4
MATH-182
Calculus II (General Education – Mathematical Perspective B)
This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in MATH-181 or MATH-181A or equivalent course. Co-requisites: MATH-182R or equivalent course.) Lecture 6 (Fall, Spring).
4
YOPS-10
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring).
0
 
General Education – First-Year Writing (WI)
3
Second Year
BIOL-135
Introduction to Bioinformatics Programming
Computer programming in the life sciences is used for modeling and data analysis across all fields. In this course, students will learn the fundamentals of computer programming and apply it to solve real problems in the life sciences. Breaking down problems, common syntax, and thoughtful decisions on proper use of data structures will be emphasized. (UGRD-COS) Lab 2, Lecture 2 (Fall).
3
BIOL-206
Molecular Biology
This course will address the fundamental concepts of Molecular Biology. Class discussions, assignments, and projects will explore the structure and function of biologically important molecules (DNA, RNA and proteins) in a variety of cellular and molecular processes. Students in this course will explore the molecular interactions that facilitate the storage, maintenance and repair of DNA and processes that drive the flow of genetic information and evolution. Students in this course will gain an understanding of various molecular mechanisms, structure/function relationships, and processes as they relate to molecular biology. The foundational molecular concepts in this course will be built upon in a variety of upper-level biology courses. (Prerequisite:(BIOL-101,BIOL-102,BIOL-103&BIOL-104) or (BIOL-121&BIOL-122) or (BIOL-123,BIOL-124,BIOL-125&BIOL-126)or equivalent courses with a grade of C- or higher. Co-requisite:(CHMG-141&CHMG-145)or(CHEM-151&CHEM-155) or CHMG-131 or equivalent courses.) Lecture 3 (Fall, Spring).
3
BIOL-216
Molecular Biology Laboratory
This laboratory course will address the fundamental concepts of Molecular Biology. Students in this laboratory will complement their understanding of core concepts in Molecular Biology through the implementation and practice of laboratory techniques used by Molecular Biologists. Laboratory techniques and projects will focus on recombinant DNA technology and the detection and tracking of biomolecules such as DNA, RNA and proteins. (Prerequisite:(BIOL-101&BIOL-102&BIOL-103&BIOL-104)or(BIOL-121&BIOL-122)or(BIOL-123&BIOL-124&BIOL-125&BIOL-126)or equivalent courses w/ grade of C- or higher. Co-requisite:BIOL-206&((CHMG-141&CHMG-145)or(CHEM-151&CHEM-155)orCHMG-131)or equivalent courses.) Lab 3 (Fall, Spring).
1
BIOL-230
Bioinformatics Languages
This is an introductory course in languages commonly used in bioinformatics and their application to biological data. We will investigate the use of multiple languages for processing sequence and "-omics" data, building analysis pipelines, integrating languages, managing a variety of biological data types, and providing effective interfaces to existing tools for analysis of these data. The course is largely based around live-code demonstration, in-class assisted coding assignments, and a student-designed final class project. (Prerequisites: BIOL-135 or equivalent course.) Lecture 2, Studio 2 (Spring).
3
BIOL-321
Genetics
Introduction to the principles of inheritance; the study of genes and chromosomes at molecular, cellular, organismal, and population levels. (Prerequisites: (BIOL-206 and BIOL-216) or BIOL-201 or BIOL-202 or BIOG-240 or equivalent courses.) Lecture 3, Recitation 1 (Fall, Spring, Summer).
3
CHMO-231
Organic Chemistry I (General Education)
This course is a study of the structure, nomenclature, reactions and synthesis of the following functional groups: alkanes, alkenes, alkynes. This course also introduces chemical bonding, IR and NMR spectroscopy, acid and base reactions, stereochemistry, nucleophilic substitution reactions, and alkene and alkyne reactions. In addition, the course provides an introduction to the use of mechanisms in describing and predicting organic reactions. (Prerequisites: CHMG-142 or CHMG-131 or equivalent course. Corequisites: CHMO-235 or equivalent course.) Lecture 3 (Fall, Spring, Summer).
3
CHMO-235
Organic Chemistry Lab I (General Education)
This course trains students to perform techniques important in an organic chemistry lab. The course also covers reactions from the accompanying lecture CHMO-231. (Corequisite: CHMO-231 or equivalent course.) Lab 3 (Fall, Spring, Summer).
1
MATH-190
Discrete Mathematics for Computing (General Education)
This course introduces students to ideas and techniques from discrete mathematics that are widely used in Computer Science. Students will learn about the fundamentals of propositional and predicate calculus, set theory, relations, recursive structures and counting. This course will help increase students’ mathematical sophistication and their ability to handle abstract problems. (Co-requisites: MATH-182 or MATH-182A or MATH-172 or equivalent courses.) Lecture 3, Recitation 1 (Fall, Spring).
3
STAT-145
Introduction to Statistics I (General Education)
This course introduces statistical methods of extracting meaning from data, and basic inferential statistics. Topics covered include data and data integrity, exploratory data analysis, data visualization, numeric summary measures, the normal distribution, sampling distributions, confidence intervals, and hypothesis testing. The emphasis of the course is on statistical thinking rather than computation. Statistical software is used. (Prerequisites: Any 100 level MATH course, or NMTH-260 or NMTH-272 or NMTH-275 or (NMTH-250 with a C- or better) or a Math Placement Exam score of at least 35.) Lecture 3 (Fall, Spring, Summer).
3
 
General Education – Ethical Perspective
3
 
General Education – Artistic Perspective
3
 
General Education – Global Perspective
3
Third Year
BIOL-235
Fundamentals of Bioinformatics Programming
Computer programming in the life sciences is used for modeling and data analysis across all fields. In this course, students will learn more advanced techniques to solve life sciences modeling problems efficiently using parallelization and distributed computing. Common methods and thoughtful decisions on proper use of tools will be emphasized. (Prerequisites: BIOL-230 or equivalent course and students in COS Majors.) Lab 2, Lecture 2 (Fall).
3
BIOL-296
Ethical Issues in Biology and Medicine
This course explores major ethical issues in medicine and biology via lecture, readings, films, and presentation and discussion of cases. Students report on current events in ethics as researched on the internet or other news media. The first portion of the course is in a lecture format. Students learn about various theories of ethical analysis that are in current use. Subsequent classes are devoted to particular ethical areas. Relevant cases are given to the students for presentation in both written and oral formats. Any additional background material that may be required to discuss the cases is presented by the instructor and the remainder of the period is discussion based on the philosophical foundation provided at the beginning of the course. (Prerequisites: (BIOL-101 and BIOL-102 and BIOL-103 and BIOL-104) or (BIOL-121 and BIOL-122) or (BIOL-123 and BIOL-124 and BIOL-125 and BIOL-126) or equivalent courses.) Lecture 3 (Spring).
3
BIOL-327
Fundamental Bioinformatics Analysis
This course addresses the fundamental concepts of bioinformatics, focusing on computational analysis of nucleic acids and proteins. Utilization of computational programs for analysis of individual and multiple sequences for functional and evolutionary information will be discussed. The computational laboratory will highlight the applications available for analysis of molecular sequences. (Prerequisite: BIOL-201 or BIOL-202 or BIOL-206 or BIOG-240 or equivalent course.) Lecture 2, Studio 2 (Fall).
3
BIOL-499
Biology Co-op (summer)
Cooperative education experience for undergraduate biological sciences students. CO OP (Fall, Spring, Summer).
0
BIOL-550
High Throughput Sequencing Analysis (WI-PR)
Students will utilize commonly used bioinformatics tools to analyze a real High Throughput Sequencing data set starting with raw data, proceeding with quality control, either aligning to a reference genome or performing de novo assembly, assessing differential gene expression determination, and finally annotating their results. Weekly lab reports will be required, and a group manuscript is expected at the end of the semester. (Prerequisite: BIOL-201 or BIOL-202 or BIOL-206 or BIOG-240 or equivalent course.) Lab 2, Lecture 2 (Spring).
3
CHMB-402
Biochemistry I
This course introduces the structure and function of biological macromolecules and their metabolic pathways. The relationship between the three-dimensional structure of proteins and their function in enzymatic catalysis will be examined. Membrane structure and the physical laws that apply to metabolic processes will also be discussed. (Prerequisite: CHMO-231 or CHMO-331 or equivalent course.) Lecture 3 (Fall, Spring, Summer).
3
ISTE-230
Introduction to Database and Data Modeling
A presentation of the fundamental concepts and theories used in organizing and structuring data. Coverage includes the data modeling process, basic relational model, normalization theory, relational algebra, and mapping a data model into a database schema. Structured Query Language is used to illustrate the translation of a data model to physical data organization. Modeling and programming assignments will be required. Note: students should have one course in object-oriented programming. (Prerequisites: ISTE-120 or ISTE-200 or IGME-101 or IGME-105 or CSCI-140 or CSCI-142 or NACA-161 or NMAD-180 or BIOL-135 or GCIS-123 or GCIS-127 or equivalent course.) Lec/Lab 3 (Fall, Spring).
3
 
General Education – Social Perspective
3
 
General Education – Immersion 1, 2
6
 
Open Elective
3
Fourth Year
BIOL-340
Genomics
The overall goal of this course is to familiarize students with the theory and analysis of genomics data. Students will survey topics including the structure, organization, and expression of the genome in a diverse array of organisms ranging from microbes to humans. Students will also become familiar with the analysis of next generation ‘omics-type data through a series of computational activities and problem sets. A hands-on laboratory component will guide students through a rigorous investigation of genomes. (Prerequisites: BIOL-321 or equivalent course.) Lab 3, Lecture 3 (Fall).
4
BIOL-470
Statistical Analysis for Bioinformatics
This course is an introduction to the probabilistic models and statistical techniques used in computational molecular biology. Examples include Markov models, such as the Jukes-Cantor and Kimura evolutionary models and hidden Markov models, and multivariate models use for discrimination and classification. (Prerequisites: (MATH-161 or MATH-173 or MATH-182) and (STAT-145 or MATH-251) or equivalent courses.) Lecture 3 (Spring).
3
BIOL-500
Experiential Learning Requirement in Life Sciences
The experiential learning (EL) requirement may be fulfilled through a variety of methods including co-op, undergraduate research, summer research experiences, study abroad relevant to the major, designated EL courses, etc. All experiences must be approved by the GSOLS EL Committee. Lecture (Fall, Spring, Summer).
0
BIOL-530
Bioinformatics Algorithms
Bioinformatics Algorithms will focus on the types of analyses, tools, and databases that are available and commonly used in Bioinformatics. The labs will apply the lecture material in the analysis of real data through computer programming. (Prerequisites: BIOL-230 and BIOL-327 or equivalent courses.) Lab 2, Lecture 2 (Fall).
3
BIOL-594
Molecular Modeling and Proteomics
This course will explore two facets of protein molecules: separation and structure. The separation component will address common protein separation techniques such as 2D gel electrophoresis and chromatography. The structure component will follow the levels of protein structures, focusing on both experimental and computational methods to determine protein structures. Methods for determining primary structures such as Edman degradation method, Sanger method and mass spectrometry will be taught in lectures. Algorithms of predicting secondary structures will be introduced and implemented. Tertiary structure determination techniques such as NMR will be covered, with an emphasis on proton NMR, 13C NMR and multi-dimensional NMR. Homology modeling will be used to predict protein tertiary structures. (Prerequisite: BIOL-327 or equivalent course.) Lab 2, Lecture 2 (Spring).
3
 
General Education – Immersion 3
3
 
General Education – Elective
3
 
Open Electives
9
Total Semester Credit Hours
120

Please see General Education Curriculum (GE) for more information.

(WI) Refers to a writing intensive course within the major.

Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.

Combined Accelerated Bachelor's/Master's Degrees

The curriculum below outlines the typical course sequence(s) for combined accelerated degrees available with this bachelor's degree.

Bioinformatics and Computational Biology, BS/Bioinformatics, MS degree, typical course sequence

Course Sem. Cr. Hrs.
First Year
BIOL-123
Introduction to Biology: Organisms and Ecosystems (General Education – Elective)
This course serves as an introduction to biology for majors, focusing on the organismal, population, and ecosystem levels. Major themes include: evolution, structure and function, information flow and storage, pathways and transformations of energy and matter, and systems. The course also focuses on developing core competencies, such as applying the process of science, using quantitative reasoning, communicating, and collaborating. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.) Lecture 3 (Fall).
3
BIOL-124
Introduction to Biology: Molecules and Cells (General Education – Elective)
This course serves as an introduction to biology for majors, focusing on the molecular and cellular level. Major themes include: evolution, structure and function, information flow and storage, pathways and transformations of energy and matter, and systems. The course also focuses on developing core competencies, such as applying the process of science, using quantitative reasoning, communicating, and collaborating. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students.) Lecture 3 (Spring).
3
BIOL-125
Introduction to Biology Laboratory: Organisms and Ecosystems (General Education – Elective)
This course is an introduction to laboratory work in life sciences. The laboratory work is project-based, and may involve field work as well as laboratory experiments. The course is designed to show the huge scope of biology and will encompass how some molecular biology and bioinformatics techniques connect with organismal and ecological biology. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students. Co-requisites: BIOL-123 or equivalent course.) Lab 3 (Fall).
1
BIOL-126
Introduction to Biology Laboratory: Molecules and Cells (General Education – Elective)
This course is an introduction to laboratory work in life sciences. The laboratory work is project based, and the subject matter of the project(s) may vary. The course is designed to show the huge scope of biology and will encompass some molecular biology and bioinformatics techniques connect with organismal and ecological biology. (This course is restricted to BIOL-BS, BIOTECH-BS, ENVS-BS, BIOINFO-BS, BIOMED-BS, BIOCHEM-BS, or NEURO-BS students. Co-requisites: BIOL-124 or equivalent course.) Lab 3 (Spring).
1
BIOL-130
Introduction to Bioinformatics
This course will explore topics in the field of bioinformatics including tools and resources used by the discipline, including direct experience with the common user environment. Lecture 3 (Fall).
3
CHMG-141
General & Analytical Chemistry I (General Education – Natural Science Inquiry Perspective)
This is a general chemistry course for students in the life and physical sciences. College chemistry is presented as a science based on empirical evidence that is placed into the context of conceptual, visual, and mathematical models. Students will learn the concepts, symbolism, and fundamental tools of chemistry necessary to carry on a discourse in the language of chemistry. Emphasis will be placed on the relationship between atomic structure, chemical bonds, and the transformation of these bonds through chemical reactions. The fundamentals of organic chemistry are introduced throughout the course to emphasize the connection between chemistry and the other sciences. Lecture 3 (Fall, Spring, Summer).
3
CHMG-142
General & Analytical Chemistry II (General Education – Scientific Principles Perspective)
The course covers the thermodynamics and kinetics of chemical reactions. The relationship between energy and entropy change as the driving force of chemical processes is emphasized through the study of aqueous solutions. Specifically, the course takes a quantitative look at: 1) solubility equilibrium, 2) acid-base equilibrium, 3) oxidation-reduction reactions and 4) chemical kinetics. (Prerequisites: CHMG-141 or CHMG-131 or equivalent course.) Lecture 3 (Fall, Spring, Summer).
3
CHMG-145
General & Analytical Chemistry I Lab (General Education – Natural Science Inquiry Perspective)
The course combines hands-on laboratory exercises with workshop-style problem sessions to complement the CHMG-141 lecture material. The course emphasizes laboratory techniques and data analysis skills. Topics include: gravimetric, volumetric, thermal, titration and spectrophotometric analyses, and the use of these techniques to analyze chemical reactions. (Corequisite: CHMG-141 or CHMG-131 or equivalent course.) Lab 3 (Fall, Spring, Summer).
1
CHMG-146
General & Analytical Chemistry II Lab (General Education – Scientific Principles Perspective)
The course combines hands-on laboratory exercises with workshop-style problem sessions to complement the CHMG-142 lecture material. The course emphasizes the use of experiments as a tool for chemical analysis and the reporting of results in formal lab reports. Topics include the quantitative analysis of a multicomponent mixture using complexation and double endpoint titration, pH measurement, buffers and pH indicators, the kinetic study of a redox reaction, and the electrochemical analysis of oxidation reduction reactions. (Prerequisites: CHMG-131 or CHMG-141 or equivalent course. Corequisites: CHMG-142 or equivalent course.) Lab 3 (Fall, Spring, Summer).
1
MATH-181
Project-Based Calculus I (General Education – Mathematical Perspective A)
This is the first in a two-course sequence intended for students majoring in mathematics, science, or engineering. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers functions, limits, continuity, the derivative, rules of differentiation, applications of the derivative, Riemann sums, definite integrals, and indefinite integrals. (Prerequisites: MATH-111 or (NMTH-220 and NMTH-260 or NMTH-272 or NMTH-275) or equivalent courses with a minimum grade of B-, or a score of at least 60% on the RIT Mathematics Placement Exam. Co-requisites: MATH-181R or equivalent course.) Lecture 6 (Fall, Spring).
4
MATH-182
Project-Based Calculus II (General Education – Mathematical Perspective B)
This is the second in a two-course sequence. It emphasizes the understanding of concepts, and using them to solve physical problems. The course covers techniques of integration including integration by parts, partial fractions, improper integrals, applications of integration, representing functions by infinite series, convergence and divergence of series, parametric curves, and polar coordinates. (Prerequisites: C- or better in MATH-181 or MATH-181A or equivalent course. Co-requisites: MATH-182R or equivalent course.) Lecture 6 (Fall, Spring).
4
YOPS-10
RIT 365: RIT Connections
RIT 365 students participate in experiential learning opportunities designed to launch them into their career at RIT, support them in making multiple and varied connections across the university, and immerse them in processes of competency development. Students will plan for and reflect on their first-year experiences, receive feedback, and develop a personal plan for future action in order to develop foundational self-awareness and recognize broad-based professional competencies. (This class is restricted to incoming 1st year or global campus students.) Lecture 1 (Fall, Spring).
0
 
General Education – First-Year Writing (WI)
3
Second Year
BIOL-135
Introduction to Bioinformatics Programming
Computer programming in the life sciences is used for modeling and data analysis across all fields. In this course, students will learn the fundamentals of computer programming and apply it to solve real problems in the life sciences. Breaking down problems, common syntax, and thoughtful decisions on proper use of data structures will be emphasized. (UGRD-COS) Lab 2, Lecture 2 (Fall).
3
BIOL-206
Molecular Biology
This course will address the fundamental concepts of Molecular Biology. Class discussions, assignments, and projects will explore the structure and function of biologically important molecules (DNA, RNA and proteins) in a variety of cellular and molecular processes. Students in this course will explore the molecular interactions that facilitate the storage, maintenance and repair of DNA and processes that drive the flow of genetic information and evolution. Students in this course will gain an understanding of various molecular mechanisms, structure/function relationships, and processes as they relate to molecular biology. The foundational molecular concepts in this course will be built upon in a variety of upper-level biology courses. (Prerequisite:(BIOL-101,BIOL-102,BIOL-103&BIOL-104) or (BIOL-121&BIOL-122) or (BIOL-123,BIOL-124,BIOL-125&BIOL-126)or equivalent courses with a grade of C- or higher. Co-requisite:(CHMG-141&CHMG-145)or(CHEM-151&CHEM-155) or CHMG-131 or equivalent courses.) Lecture 3 (Fall, Spring).
3
BIOL-216
Molecular Biology Laboratory
This laboratory course will address the fundamental concepts of Molecular Biology. Students in this laboratory will complement their understanding of core concepts in Molecular Biology through the implementation and practice of laboratory techniques used by Molecular Biologists. Laboratory techniques and projects will focus on recombinant DNA technology and the detection and tracking of biomolecules such as DNA, RNA and proteins. (Prerequisite:(BIOL-101&BIOL-102&BIOL-103&BIOL-104)or(BIOL-121&BIOL-122)or(BIOL-123&BIOL-124&BIOL-125&BIOL-126)or equivalent courses w/ grade of C- or higher. Co-requisite:BIOL-206&((CHMG-141&CHMG-145)or(CHEM-151&CHEM-155)orCHMG-131)or equivalent courses.) Lab 3 (Fall, Spring).
1
BIOL-230
Bioinformatics Languages
This is an introductory course in languages commonly used in bioinformatics and their application to biological data. We will investigate the use of multiple languages for processing sequence and "-omics" data, building analysis pipelines, integrating languages, managing a variety of biological data types, and providing effective interfaces to existing tools for analysis of these data. The course is largely based around live-code demonstration, in-class assisted coding assignments, and a student-designed final class project. (Prerequisites: BIOL-135 or equivalent course.) Lecture 2, Studio 2 (Spring).
3
BIOL-321
Genetics
Introduction to the principles of inheritance; the study of genes and chromosomes at molecular, cellular, organismal, and population levels. (Prerequisites: (BIOL-206 and BIOL-216) or BIOL-201 or BIOL-202 or BIOG-240 or equivalent courses.) Lecture 3, Recitation 1 (Fall, Spring, Summer).
3
CHMO-231
Organic Chemistry I (General Education – Elective)
This course is a study of the structure, nomenclature, reactions and synthesis of the following functional groups: alkanes, alkenes, alkynes. This course also introduces chemical bonding, IR and NMR spectroscopy, acid and base reactions, stereochemistry, nucleophilic substitution reactions, and alkene and alkyne reactions. In addition, the course provides an introduction to the use of mechanisms in describing and predicting organic reactions. (Prerequisites: CHMG-142 or CHMG-131 or equivalent course. Corequisites: CHMO-235 or equivalent course.) Lecture 3 (Fall, Spring, Summer).
3
CHMO-235
Organic Chemistry Lab I (General Education – Elective)
This course trains students to perform techniques important in an organic chemistry lab. The course also covers reactions from the accompanying lecture CHMO-231. (Corequisite: CHMO-231 or equivalent course.) Lab 3 (Fall, Spring, Summer).
1
MATH-190
Discrete Mathematics for Computing (General Education – Elective)
This course introduces students to ideas and techniques from discrete mathematics that are widely used in Computer Science. Students will learn about the fundamentals of propositional and predicate calculus, set theory, relations, recursive structures and counting. This course will help increase students’ mathematical sophistication and their ability to handle abstract problems. (Co-requisites: MATH-182 or MATH-182A or MATH-172 or equivalent courses.) Lecture 3, Recitation 1 (Fall, Spring).
3
STAT-145
Introduction to Statistics I (General Education – Elective)
This course introduces statistical methods of extracting meaning from data, and basic inferential statistics. Topics covered include data and data integrity, exploratory data analysis, data visualization, numeric summary measures, the normal distribution, sampling distributions, confidence intervals, and hypothesis testing. The emphasis of the course is on statistical thinking rather than computation. Statistical software is used. (Prerequisites: Any 100 level MATH course, or NMTH-260 or NMTH-272 or NMTH-275 or (NMTH-250 with a C- or better) or a Math Placement Exam score of at least 35.) Lecture 3 (Fall, Spring, Summer).
3
 
General Education – Artistic Perspective
3
 
General Education – Ethical Perspective
3
 
General Education – Global Perspective
3
Third Year
BIOL-235
Fundamentals of Bioinformatics Programming
Computer programming in the life sciences is used for modeling and data analysis across all fields. In this course, students will learn more advanced techniques to solve life sciences modeling problems efficiently using parallelization and distributed computing. Common methods and thoughtful decisions on proper use of tools will be emphasized. (Prerequisites: BIOL-230 or equivalent course and students in COS Majors.) Lab 2, Lecture 2 (Fall).
3
BIOL-296
Ethical Issues in Biology and Medicine
This course explores major ethical issues in medicine and biology via lecture, readings, films, and presentation and discussion of cases. Students report on current events in ethics as researched on the internet or other news media. The first portion of the course is in a lecture format. Students learn about various theories of ethical analysis that are in current use. Subsequent classes are devoted to particular ethical areas. Relevant cases are given to the students for presentation in both written and oral formats. Any additional background material that may be required to discuss the cases is presented by the instructor and the remainder of the period is discussion based on the philosophical foundation provided at the beginning of the course. (Prerequisites: (BIOL-101 and BIOL-102 and BIOL-103 and BIOL-104) or (BIOL-121 and BIOL-122) or (BIOL-123 and BIOL-124 and BIOL-125 and BIOL-126) or equivalent courses.) Lecture 3 (Spring).
3
BIOL-327
Fundamental Bioinformatics Analysis
This course addresses the fundamental concepts of bioinformatics, focusing on computational analysis of nucleic acids and proteins. Utilization of computational programs for analysis of individual and multiple sequences for functional and evolutionary information will be discussed. The computational laboratory will highlight the applications available for analysis of molecular sequences. (Prerequisite: BIOL-201 or BIOL-202 or BIOL-206 or BIOG-240 or equivalent course.) Lecture 2, Studio 2 (Fall).
3
BIOL-499
Biology Co-op (summer)
Cooperative education experience for undergraduate biological sciences students. CO OP (Fall, Spring, Summer).
0
BIOL-550
High Throughput Sequencing Analysis (WI-PR)
Students will utilize commonly used bioinformatics tools to analyze a real High Throughput Sequencing data set starting with raw data, proceeding with quality control, either aligning to a reference genome or performing de novo assembly, assessing differential gene expression determination, and finally annotating their results. Weekly lab reports will be required, and a group manuscript is expected at the end of the semester. (Prerequisite: BIOL-201 or BIOL-202 or BIOL-206 or BIOG-240 or equivalent course.) Lab 2, Lecture 2 (Spring).
3
CHMB-402
Biochemistry I
This course introduces the structure and function of biological macromolecules and their metabolic pathways. The relationship between the three-dimensional structure of proteins and their function in enzymatic catalysis will be examined. Membrane structure and the physical laws that apply to metabolic processes will also be discussed. (Prerequisite: CHMO-231 or CHMO-331 or equivalent course.) Lecture 3 (Fall, Spring, Summer).
3
ISTE-230
Introduction to Database and Data Modeling
A presentation of the fundamental concepts and theories used in organizing and structuring data. Coverage includes the data modeling process, basic relational model, normalization theory, relational algebra, and mapping a data model into a database schema. Structured Query Language is used to illustrate the translation of a data model to physical data organization. Modeling and programming assignments will be required. Note: students should have one course in object-oriented programming. (Prerequisites: ISTE-120 or ISTE-200 or IGME-101 or IGME-105 or CSCI-140 or CSCI-142 or NACA-161 or NMAD-180 or BIOL-135 or GCIS-123 or GCIS-127 or equivalent course.) Lec/Lab 3 (Fall, Spring).
3
 
General Education – Social Perspective
3
 
General Education – Immersion 1, 2
6
 
Open Elective
3
Fourth Year
BIOL-340
Genomics
The overall goal of this course is to familiarize students with the theory and analysis of genomics data. Students will survey topics including the structure, organization, and expression of the genome in a diverse array of organisms ranging from microbes to humans. Students will also become familiar with the analysis of next generation ‘omics-type data through a series of computational activities and problem sets. A hands-on laboratory component will guide students through a rigorous investigation of genomes. (Prerequisites: BIOL-321 or equivalent course.) Lab 3, Lecture 3 (Fall).
4
BIOL-470
Statistical Analysis for Bioinformatics
This course is an introduction to the probabilistic models and statistical techniques used in computational molecular biology. Examples include Markov models, such as the Jukes-Cantor and Kimura evolutionary models and hidden Markov models, and multivariate models use for discrimination and classification. (Prerequisites: (MATH-161 or MATH-173 or MATH-182) and (STAT-145 or MATH-251) or equivalent courses.) Lecture 3 (Spring).
3
BIOL-500
Experiential Learning Requirement in Life Sciences
The experiential learning (EL) requirement may be fulfilled through a variety of methods including co-op, undergraduate research, summer research experiences, study abroad relevant to the major, designated EL courses, etc. All experiences must be approved by the GSOLS EL Committee. Lecture (Fall, Spring, Summer).
0
BIOL-630
Bioinformatics Algorithms
Bioinformatics Algorithms will focus on the types of analyses, tools, and databases that are available and commonly used in Bioinformatics. The labs will apply the lecture material in the analysis of real data through computer programming. (This course is restricted to students in the BIOINFO-MS, BIOINFO-BS/MS program.) Lab 3, Lecture 2 (Fall).
3
BIOL-694
Molecular Modeling and Proteomics
This course will explore two facets of protein molecules: their separation and their structure. The structure component will build upon information from earlier bioinformatics courses. Protein separation techniques will be addressed in lectures with descriptions of 2D gel electrophoresis and chromatography. Algorithms of protein secondary structure prediction will be implemented. Experimental techniques for tertiary structure determination such as NMR will be covered. The course will also include the analysis of inter-molecular interactions, such as ligand/receptor pairing, by employing software that permits modeling of molecular docking experiments. (Prerequisite: BIOL-327 or equivalent course or student standing in BIOINFO-MS.) Lab 2, Lecture 2 (Spring).
3
BIOL-790
Research and Thesis
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course requires permission of the Instructor to enroll.) Thesis (Fall, Spring, Summer).
2
 
Open Electives
9
 
General Education – Immersion 3
3
 
General Education – Elective
3
Fifth Year
BIOL-625
Ethics in Bioinformatics
This course will be focused on individual and organizational responsibilities in bioinformatics research, product development, product commercialization and clinical and consumer genetic testing. (This course is restricted to students in the BIOINFO-MS, BIOINFO-BS/MS program.) Lecture 3 (Fall).
3
BIOL-635
Bioinformatics Seminar
The course provides opportunities for students and faculty to develop and share professional interests while discussing current trends and developments in bioinformatics. Material for this course will be drawn from the current scientific literature. (This course is restricted to students in the BIOINFO-MS, BIOINFO-BS/MS program.) Lecture 3 (Fall).
3
BIOL-672
Computational Statistics and Data Science Methods
This course will introduce traditional multivariate statistical methods and multi-model inference, as well as iterative computational algorithms (i.e. Bayesian methods and machine learning) appropriate for graduate students conducting or planning to conduct a graduate research project. The course will focus on the proper application of methods to a sample data sets using statistical programming software and graphics and will forego the more in-depth analytical mathematical exposition that you might see in a math course, so that we can cover a larger variety of methods and spend more time implementing them in code. Practical examples will often derive from the fields of biology, environmental science, or medicine, however the statistical methods we cover will also have much broader application within modern data science. The ultimate goal will be to learn when and where to correctly apply a given method to real questions about real data. Class time will be devoted to introductory lecture, programming language demonstrations with a common dataset, and open discussions of potential applications, including in-class studio hours to help with homework. Students should be prepared to learn to write code scripts that will manipulate statistical tests and graphical output. However, no background experience with programming is assumed. All software used in the course is open-source and students will be required to set up and run weekly assignments on their own laptop computer or on a computer borrowed from the library or RIT’s computer lab. (Prerequisites: STAT-145 or equivalent course or graduate student standing.) Lecture 2, Studio 2 (Fall, Spring).
3
BIOL-790
Research and Thesis
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor. (This course requires permission of the Instructor to enroll.) Thesis (Fall, Spring, Summer).
4
 
Graduate Program Electives‡
9
Total Semester Credit Hours
144

Please see General Education Curriculum (GE) for more information.

(WI) Refers to a writing intensive course within the major.

* Please see Wellness Education Requirement for more information. Students completing bachelor's degrees are required to complete two different Wellness courses.

‡ Graduate electives may be any graduate-level course related to the field of bioinformatics. Consult academic advisers for assistance in course selection.

Admissions and Financial Aid

This program is STEM designated when studying on campus and full time.

First-Year Admission

A strong performance in a college preparatory program is expected. This includes:

  • 4 years of English
  • 3 years of social studies and/or history
  • 3 years of mathematics is required and must include algebra, geometry, and algebra 2/trigonometry. Pre-calculus is recommended.
  • 2-3 years of science is required and must include biology and chemistry.

Transfer Admission

Transfer course recommendations without associate degree
Courses in liberal arts, sciences, math, and computing

Appropriate associate degree programs for transfer
AS degree in biotechnology or liberal arts with biology

Learn How to Apply

Financial Aid and Scholarships

100% of all incoming first-year and transfer students receive aid.

RIT’s personalized and comprehensive financial aid program includes scholarships, grants, loans, and campus employment programs. When all these are put to work, your actual cost may be much lower than the published estimated cost of attendance.
Learn more about financial aid and scholarships

Research

Undergraduate Research Opportunities

Many students join research labs and can engage in research projects starting as early as their first year. Participation in undergraduate bioinformatics research leads to the development of real-world lab techniques, enhanced problem-solving skills, and broader career opportunities. Our students have opportunities to travel to national conferences for presentations and also become contributing authors on peer-reviewed manuscripts. Explore the variety of life science undergraduate research happening at RIT.

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