Akram Mendez's Projects
My personal portfolio repository
Convolutional neural network analysis for predicting DNA sequence activity.
Conda recipes for the bioconda channel.
Bioinformatics Workbook repository
A list of useful bioinformatics resources
ChIP-seq analysis notes from Ming Tang
General repository with custom scripts for data processing, bioinformatic workflows and downstream analysis
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Bayesian haplotype-based polymorphism discovery and genotyping.
General Collection of my How-To Notes
Source code and analysis repository used in "Global loss of cellular m6A RNA methylation following infection with different SARS-CoV-2 variants"
Collection of my Machine learning Notes, Scripts and Implementation Examples of common ML algorithms
Repository to host tool-specific module files for the Nextflow DSL2 community!
Python and C++ code for reading and writing genomics data.
RNAseq analysis notes from Ming Tang
RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.
scRNAseq analysis notes from Ming Tang
Single cell current best practices tutorial case study for the paper:Luecken and Theis, "Current best practices in single-cell RNA-seq analysis: a tutorial"
A brief tutorial of how to implement SQUAD for the qualitative analysis of regulatory networks
Dynamic network models has been used in biological contexts to represent complex regulatory interactions between molecules. Discrete Boolean methods are often used as a first modeling approximation. However in some biological contexts they are not sufficient to represent some behaviors as that which depends on threshold activation or molecular gradients. In these cases, ordinary differential equations are preferred but their application need the knowledge of kinetic parameters. Here we describe a continuous ODE system called Standardized Qualitative Analysis of Dynamics (SQUAD) as a first approximation to simulate continuous models without the need of kinetic parameters.
A collection of scripts for processing fastq files in ways to improve de novo transcriptome assemblies, and for evaluating those assemblies.
webinR en español, conceptos básicos de R y tidyverse