G (1-0-5)
Thursdays 3-4 30 pm ET
Online
View on Canvas
Description:
Designed for grant proposal and research publication student writers, this course presents a general overview as well as the level of detail for creating well-written scientific documents. Each component of the grant and research publication writing process will be addressed, including: documenting your laboratory research data and observations in LaTeX; writing measurable objectives; making high quality figures in Python and MatLab. Developing testable hypotheses and an empiric research plan to test them.
Components of grant proposal application
Goals: Prepare a complete grant proposal (computation + any field you are working in) to an agency of choice with the instructor. This includes a 1 page significance and specific aims section, 5 page research plan and a minimum 2 year $80,000 budget with multiple categories. Peer review (with the instructor) several examples of publicly posted prototype grant proposals. Participate in a mock online study section as reviewers of proposals from other students in the course and assign scores and prepare summary statements. Learn transferable skills for writing high-quality research papers.
Topics include:
Fields
Biological: Recombinant DNA mutation & complementation, cellular pathways, next-generation sequencing, mass spectrometry for proteomics, high performance liquid chromatography for metabolomics, sequence alignments, BLAST searches, KEGG pathway analyses, homology mapping
Computational and engineering: Convolutional neural networks, Bayesian inference, deep learning, Hidden Markov Models, auto-encoders, recurrent neural networks, Reinforcement learning, Markov Decision Process, image processing, bioinformatics, clustering and classification, kmeans, Human-computer interactions, Sensors, R, Perl
Clinical: Biomarker assays and interpretations, surrogate endpoints, interventions and treatments, adverse events, randomized control trials
Statistical: p-value, students’ t-test, Pearson’s correlation coefficient, Principal Component Analysis, causal inference, Mann-Whitney U Test
Art: Painting, architecture, sculpture, design, literature, music, performing arts + technology projects and funding
Learning outcomes
Start date: April 8th, 2021
End date: May 20th, 2021
Prerequisites: Students and participants interested in learning, updating or improving their scientific writing skills are welcome to enroll. Critical analysis of peer-reviewed research publications and National Institutes of Health (NIH) and National Science Foundation (NSF) grant proposals are a plus.
Notes
1. Please make notes during class relevant to each topic that you wish to discuss more. Details on accessing and editing class notes with LaTeX, will be shared
2. Opportunity to engage with invited speakers and program managers and center directors at the forefront of funding agencies (NIH, NSF, DARPA etc.), technology (IBM, Google, Apple etc.) and non-profit foundations.
Textbook and research articles reading
There is no required textbook for the course. All required articles and readings will be available for download from the MIT CANVAS site.
Suggested resources: