This is the second year that I have taught “Clinical Bioinformatics” at UMKC. By design, the class has no biology or computational prerequisites, I want to “use informatics to teach biology and biology to teach informatics”. Each student is assigned a clinically significant human gene which they use for most of the exercises in the class. They also identify a disease or phenotype associated variant in the gene and use the associated amino acid change in the later sessions of the class. I require the students to document many of their assignments in blog format.
Because one of my first introductions to bioinformatics was three dimensional protein modeling, I am always eager to see their 3D protein structure assignment. This year I want highlight their work on this assignment and share it. They each have developed a personal visual style and narrative voice in their blogs. They did a great job in meeting the rubrics for this assignment. Below are images from their blog posts as well as hyperlinks to the full entry. I’m very proud of these students and wish to congratulate each of them.
Jeremy Provance has been using TP53 as his gene, with the site of one disease associated variant highlighted in red.
Sally Fowler has been studying ASPA. Her screen shot shows an overlay with the sequence analysis in DNASTAR.
Rei Sekiguchi has examined PAH, shown here as a dimer.
Isaac Jonas has used DMD, a very complex protein, for his exercises.
Megha Shah Desani worked with CYP2C19, which we found is not fully covered in some online resources.
