{"id":141,"date":"2025-03-10T14:50:46","date_gmt":"2025-03-10T18:50:46","guid":{"rendered":"https:\/\/sites.bu.edu\/bmsip\/?page_id=141"},"modified":"2026-08-03T13:45:57","modified_gmt":"2026-08-03T17:45:57","slug":"curriculum","status":"publish","type":"page","link":"https:\/\/sites.bu.edu\/bmsip\/curriculum\/","title":{"rendered":"Curriculum"},"content":{"rendered":"<p>The Bioinformatics MS Program equips students with the computational, statistical, and experimental skills needed to analyze <strong>complex biological data<\/strong>. With a focus on <strong>genomics <\/strong>and\u00a0<strong>transcriptomics,<\/strong> the curriculum integrates molecular biology, computer science, and data science, including machine learning. We incorporate a variety of methods including behavioral driven design, unit testing, and the AI assessment scale to instill responsible, and transparent usage of <strong>agentic coding harnesse<\/strong>s and LLM-based tools. Students gain hands-on experience using agentic coding harnesses with a strong emphasis on complementing their understanding of the material and rigorously reviewing aspects of computational research that remain the domain of researchers.<\/p>\n<p>Students develop computational expertise in working with key bioinformatics frameworks and tools for <strong>data wrangling<\/strong>, <strong>statistical analysis<\/strong>, <strong>visualization<\/strong>,<strong> reproducible science<\/strong> tools and practices, and <strong>machine learning<\/strong>:<\/p>\n<ul>\n<li aria-level=\"1\"><strong>Programming languages:<\/strong> R, Python, SQL, shell scripting, agentic coding harnesses (Claude)<\/li>\n<li aria-level=\"1\"><strong>Computational Environments:<\/strong> UNIX\/Linux, conda, pip, containerization, high performance cluster (HPC)<\/li>\n<li aria-level=\"1\"><strong>Development Environments:<\/strong> RStudio, VSCode, Computational notebooks (Jupyter, RNotebooks), Relational databases\/SQL<\/li>\n<li aria-level=\"1\"><strong>Reproducibility Practices:<\/strong> Workflow managers (Nextflow\/snakemake),\u00a0 git\/GitHub<\/li>\n<li aria-level=\"1\"><strong>Science Communication:<\/strong> Data visualization (matplotlib\/ggplot), RMarkdown, RShiny, Elementary web application programming<\/li>\n<li aria-level=\"1\"><strong>Sequence Analysis:<\/strong> Next generation sequence alignment (bwa\/bowtie\/STAR), BLAST, Multiple Sequence Alignment, Sequence motif analysis, Phylogenetic algorithms<\/li>\n<\/ul>\n<p>Students gain hands-on experience with modern genomics datatypes, with a focus on next generation sequencing (NGS), including:<b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><strong>Bulk &amp; single cell RNA-Seq<\/strong><\/li>\n<li aria-level=\"1\"><strong>Differential expression analysis<\/strong><\/li>\n<li aria-level=\"1\"><strong>ChIP-Seq<\/strong><strong><\/strong><\/li>\n<\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<p>They also become familiar with major bioinformatics databases:<b><\/b><\/p>\n<ul>\n<li aria-level=\"1\"><strong>Sequence Databases:<\/strong> NCBI, EBI, ENSEMBL<\/li>\n<li aria-level=\"1\"><strong>Genome Browsers &amp; Visualization:<\/strong> Integrated Genome Viewer (IGV), UCSC Genome Browser<\/li>\n<li aria-level=\"1\"><strong>Biological Data Repositories:<\/strong> Short Read Archive (SRA), Gene Expression Omnibus (GEO)<\/li>\n<li aria-level=\"1\"><strong>Disease Databases:<\/strong> Open Targets Platform, Open Targets Genetics, OMIM<\/li>\n<li aria-level=\"1\"><strong>Biological Annotation Databases:<\/strong> Gene Ontology, BioGRID, STRING, Ingenuity (IPA)<\/li>\n<\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<ul><\/ul>\n<p>The program emphasizes translational bioinformatics, training students to critically evaluate scientific literature and develop research proposals applying bioinformatics to medical interventions. With a strong foundation in computational biology, graduates are well-prepared for careers in biotechnology, biomedical research, and computational medicine.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>The Bioinformatics MS Program equips students with the computational, statistical, and experimental skills needed to analyze complex biological data. With a focus on genomics and\u00a0transcriptomics, the curriculum integrates molecular biology, computer science, and data science, including machine learning. We incorporate a variety of methods including behavioral driven design, unit testing, and the AI assessment scale [&hellip;]<\/p>\n","protected":false},"author":7437,"featured_media":0,"parent":0,"menu_order":6,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/pages\/141"}],"collection":[{"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/users\/7437"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/comments?post=141"}],"version-history":[{"count":8,"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/pages\/141\/revisions"}],"predecessor-version":[{"id":261,"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/pages\/141\/revisions\/261"}],"wp:attachment":[{"href":"https:\/\/sites.bu.edu\/bmsip\/wp-json\/wp\/v2\/media?parent=141"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}