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Happiness is good health and a bad memory.
♟️
Happiness is good health and a bad memory.
  • University of Tokyo
  • Tokyo, Japan
  • 01:24 (UTC +09:00)

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waldenblue/README.md

🔬 About Me

I'm a passionate bioinformatics researcher dedicated to leveraging computational methods to solve biological problems. My work focuses on genomics, proteomics, and systems biology, with a particular interest in developing novel algorithms for biological data analysis.

🧬 Research Interests

  • Genomics & Transcriptomics: RNA-seq analysis, variant calling, and genome assembly
  • Structural Bioinformatics: Protein structure prediction and molecular dynamics simulations
  • Systems Biology: Network analysis and pathway enrichment studies
  • Machine Learning in Biology: Deep learning applications for biological sequence analysis
  • Phylogenetics: Evolutionary analysis and comparative genomics

🛠️ Technical Skills

Programming Languages

Python R Bash SQL

Bioinformatics Tools & Frameworks

  • Sequence Analysis: BLAST, BWA, STAR, HISAT2, Bowtie2
  • Genomics: GATK, SAMtools, BCFtools, VCFtools
  • RNA-seq: DESeq2, edgeR, Salmon, Kallisto
  • Structural Biology: PyMOL, ChimeraX, GROMACS, OpenMM
  • Machine Learning: scikit-learn, TensorFlow, PyTorch, Keras
  • Data Visualization: matplotlib, seaborn, ggplot2, plotly

Databases & Resources

  • NCBI (GenBank, PubMed, SRA)
  • UniProt, PDB, Pfam
  • KEGG, GO, Reactome
  • TCGA, GTEx, UK Biobank

🔥 Current Projects

  • 🧪 GenomeAnalyzer: A comprehensive pipeline for whole genome sequencing analysis
  • 🦠 ProteinFoldNet: Deep learning model for protein secondary structure prediction
  • 📈 BioVizToolkit: Interactive visualization tools for biological data
  • 🌱 PlantGenomics: Comparative genomics analysis of plant species

📊 GitHub Stats

WaldenBlue's GitHub stats Top Languages

🏆 Achievements

  • 📝 Published research in peer-reviewed bioinformatics journals
  • 🎤 Presented findings at international bioinformatics conferences
  • 🏅 Contributor to open-source bioinformatics projects
  • 🎓 Certified in computational biology and data science

📚 Recent Publications

  • "Novel approaches to protein structure prediction using deep learning" - Bioinformatics Journal (2024)
  • "Comparative genomics analysis reveals evolutionary patterns in plant genomes" - Nature Computational Biology (2023)
  • "Machine learning applications in RNA-seq data analysis" - BMC Bioinformatics (2023)

🎯 Goals for 2025

  • Develop a new algorithm for multi-omics data integration
  • Contribute to 5 open-source bioinformatics projects
  • Complete advanced course in structural bioinformatics
  • Present research at the ISMB conference

💡 "In the intersection of biology and computation lies the future of medicine"

📧 Feel free to reach out for collaborations or discussions about bioinformatics!

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  1. naosei1456 naosei1456 Public

    Introducción GitHub

    Kotlin 1