Quikcall
Jr Developer, Biologist specialized in Bioinformatics; Python, C#, C++, X++; Problem Solver; Favorite hobbies are ✈️, 🎮 and 🎴.
Pinned Repositories
Metabolic-Network-X
Development of the class MetabolicNetworkX, using the libraries NetworkX, ElementTree XML, Pyvis and Matplotlib, to allow the visualization and manipulation of metabolic networks inputted (different formats allowed), as well as study their topology using 4 different metrics: Degree Distribution, Shortest Path Analysis, Clustering Coefficient & Hubs and Centrality Measures. Developed for the course of Advanced Algorithms for Bioinformatics.
MOSCA_webapp
Bioinformatics Master's Project - Development of a web application for the Metagenomics and trancstriptomics analytical tool MOSCA
Python-Ganda-Galo
A tic tac toe game with n*n dimensions. Developed for the course 'Introduction to Algorithms and Programming' for the Bioinformatics Master
R-pipeline-to-analyse-Metabolomics-Data
Statistical analysis, PCA & Clustering and Machine Learning methods for feature selection using Metabolomics data derived from 1H NMR spectroscopy
RNA-Seq-Analysis
Analysis of transcriptomic data resultant of Triple Negative Breast Cancer Stem Cells and Differentiated Tumor Cells aiming to find differences between expressed genes in the chromosomes in order to identify a possible drug target. Two cell lines were used, Mus musculus & Homo Sapiens. Developed for the course Advanced Algorithms for Bioinformatics.
Quikcall's Repositories
Quikcall/MOSCA_webapp
Bioinformatics Master's Project - Development of a web application for the Metagenomics and trancstriptomics analytical tool MOSCA
Quikcall/RNA-Seq-Analysis
Analysis of transcriptomic data resultant of Triple Negative Breast Cancer Stem Cells and Differentiated Tumor Cells aiming to find differences between expressed genes in the chromosomes in order to identify a possible drug target. Two cell lines were used, Mus musculus & Homo Sapiens. Developed for the course Advanced Algorithms for Bioinformatics.
Quikcall/Metabolic-Network-X
Development of the class MetabolicNetworkX, using the libraries NetworkX, ElementTree XML, Pyvis and Matplotlib, to allow the visualization and manipulation of metabolic networks inputted (different formats allowed), as well as study their topology using 4 different metrics: Degree Distribution, Shortest Path Analysis, Clustering Coefficient & Hubs and Centrality Measures. Developed for the course of Advanced Algorithms for Bioinformatics.
Quikcall/Python-Ganda-Galo
A tic tac toe game with n*n dimensions. Developed for the course 'Introduction to Algorithms and Programming' for the Bioinformatics Master
Quikcall/R-pipeline-to-analyse-Metabolomics-Data
Statistical analysis, PCA & Clustering and Machine Learning methods for feature selection using Metabolomics data derived from 1H NMR spectroscopy