HELLO, I'M
John Keith
Data Analyst & Programmer
About
MY BACKGROUND
Highly motivated Bioinformatics Masters graduate with over 3 years of experience capturing and analyzing physiological data in both research and industry. Seeking to apply my programming and analysis skills, familiarity with the life sciences field, and adaptable personality to a position involving gaining biological insight from data capture and analysis.
Education
WHERE I'VE STUDIED
2035–2035
Northeastern University - Boston, MA; Class of 2024
Master of Science; Bioinformatics
Experience
WHERE I’VE WORKED
Sep. 2023 – June 2023
Pression LLC
June 2022 - December 2022
Diagnostic Biochips, Inc.
May 2022 - December 2022
2035–2035
Northeastern University - Boston, MA; Class of 2022
Bachelor of Science; Neuroscience
GPA: 3.79
Affective and Brain Sciences Lab
July 2021 - December 2021
Shansky Lab
Skills & Languages
WHAT I BRING TO THE TABLE
Programming Languages: Bash/Linux, C, MATLAB, Python, Rust, R
Analysis Tools:
Excel, BioPython
Laboratory:
Clinical Trials; Perfusions; Brain/spinal cord extractions; Pipetting; Gel electrophoresis; PCR; Animal injection Embedded Programming: Arduino, C
Projects
This is a video I made using neuronal data (converted into midi data) that was retrieved using the neuronal probe made by DBC during a T-maze experiment with a mouse. To make the audio corresponding to the video, I applied the midi neuron plots to different channels within an AWS (audio work station), and had the different channels playing different instruments. You can also hear the different instruments (corresponding to neuronal groups within the mouse) get louder as the nueronal groups fire more.
This is a python program I coded to take a user input of a gene and a host (from a list of available genes and hosts from the unigene data set), and outputs a list of tissues that the gene is expressed in within the host organism. This program is robust, enabling the user to query a host in various different ways without breaking the program. It also uses a couple of different modules I coded with functions that allow the entire project to be fairly short and comprehensible. Please read the README.md within the project directory for more details on how to download the data file and run the program.
This is a project written in R designed to execute and compare two K-nearest neighbor machine learning algorithms from different packages. The file titled "DA5030.P1.Keith.pdf" is an R Markdown knitted pdf containing some echoed code and all of the figures/explanation of the project. The K-nearest neighbor algorithms are implimented on a dataset containing rows that represent different patients. For each row, there are several columns/features that respresent different attributes of the patient's tumor. The Knn algorithms are used to predict if the tumor is malignant or benign based on the previous diagnoses of the most similar tumors.