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followers: 10.0 following: 27.0 repos: 96.0 gists: 0.0

Name: Mahendra Singh

Type: User

Company: SCIS, JNU

Bio: Omics Data Analytics: Genomics | Transcriptomics | Proteomics | Metabolomics Bioinformatics: ML | Structural Biology 👍🏻 Learning 🔢 Coding Py | 🧘⛹️🌿

Twitter: smahendra360

Location: New Delhi, India

Hi__Waving hand animated gif Great to see you here :)

Key area of research interest: I have developed a keen interest to apply the knowledge I would gain in

  • Omics data science: the link between gene, protein and diseases
  • Data Science: ML, AI, NLP and Biological Image Analysis
  • Structural Biology: drug discovery
  • RNAi Biology: miRNA, lncRNA and eRNA

💫About Me :

  • 🌱 I am currently entering into Deep learning and AI
  • ✌️ I'm open to opportunities
  • ⚡ Fun Fact: Eat, Read, Sleep and Walk
  • 🤝 If you want any collaboration feel free to connet with me at 🌐 Discord Badge Linkedin Badge Twitter Badge
  • 👉 For more information please look back to my CV here

⚡ Technologies

Language

Python Biopython R

OS

Linux macOS

Libraries & Framework

Pandas Matplotlib NumPy scikit-learn Keras TensorFlow Bioconductor SciPy Streamlit

Notebook

Cloud and Version Control Tools

GitHub Pages Amazon AWS Docker Git Nextflow

Learning Platform

NPTEL | Future Learn | Metagenomics | MIT OpenCourseWare | Stanfordonline | Brilliant.org

References

Prof. Rita Sharma, Professor, and Thesis Supervisor, SCIS-JNU New Delhi, India. Email: [email protected] Tel:+919958312717

Prof. Shandar Ahmad, Professor, SCIS-JNU New Delhi, India. Email: [email protected] Tel: 7290889021

📈 Stats Mahendra's github activity graph

Random Quote..✍️

Thank you, for visiting my GitHub profile!!

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Mahendra Singh's Projects

biological-data-visualization icon biological-data-visualization

Biology data visualization is a branch of bioinformatics concerned with the application of computer graphics, scientific visualization, and information visualization to different areas of the life sciences. This includes visualization of sequences, genomes, alignments, phylogenies, macromolecular structures, systems biology, microscopy, and magnetic resonance imaging data. Software tools used for visualizing biological data range from simple, standalone programs to complex, integrated systems.

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