Name: Raúl Acosta Murillo
Type: User
Company: UANL / BP Research
Bio: I am a student of Genomic Biotechnology at the Universidad Autonóma de Nuevo León, Mexico; currently, I am in the penultimate year of my career.
Location: San Nicolás de los Garza
Raúl Acosta Murillo's Projects
Simulation uses F1 allele frequency for prediction of genotypic and phenotypic frequencies based on a pseudo-random number generated from time, allowing different results to be obtained based on randomness and observed frequencies.
Automatic Vaccine Design from a Protein Sequence. Can design a highly inmunogenic and safe sequence under 60 minutes. The steps are epitopes identification, antigenicity and allergenicity evaluation and peptide construction.
This code defines a program that can take voice commands, interpret them using Google's speech recognition API, and generate a text-based response using OpenAI's GPT-4.0 model. It then converts this text response into an audio file using Google's text-to-speech API and plays it using the Pygame library.
This code is an R script that loads RNA-Seq data and performs data manipulation, analysis, and visualization.
Cancer Disease Diagnostics using machine learning techniques.
Predictive modeling for disease outbreak prediction.
DNA sequence analysis tool.
DNA to Protein sequence converter
Fraud detection in credit card transactions.
Handwritten digit recognition using CNNs in Tensorflow.
Predictive modeling for house prices.
Image recognition for object detection using MNIST dataset, CNNs and hyperparameter tuning.
Phylogenetic Tree Construction using Python.
Calculate molecular descriptors based on SMILES structure
QSAR Model generation based on ChemBL target and virtual screening based on Zinc "World" subset using molecular fingerprints.
Daily analysis and selection of 500 S&P 500 stock based on moving average, MACD, boilinger bands, RSI, MSI and other indicators.
Stock market prediction using time series analysis.
Cancer detection through ML model development on tissue samples reported in Kaggle.
Prediction of gene perturbation for top 978 genes based on the database "L1000 Dataset -small molecule perturbagens- LINCS Phase 1" (LDS-1481) in the LINDS Portal.
EUFA winning team prediction
Wine quality prediction using chemical properties