Python Implementation of Phylogenetic Distances

$10-30 CAD

Cancelled

Posted over 1 year ago

$10-30 CAD

Paid on delivery

Looking for a skilled Python developer with a strong understanding of phylogenetics. The project involves implementing three specific phylogenetic distance methods: Jukes-Cantor distance, Kimura 2-parameter distance, and Tamura-Nei distance. Key Responsibilities: - Implement the specified phylogenetic distance methods in Python. - Use the Phylip data format for input. - Create detailed visualizations of the computed phylogenetic distances. Ideal Skills and Experience: - Proficient in Python programming. - Familiar with phylogenetic analysis and the specified distance methods. - Experience working with Phylip data format. - Capable of creating detailed, annotated visualizations. - Experience with phylogenetic libraries such as Biopython or DendroPy. Please include examples of similar projects you've completed in your application. The project should include phylogenetic trees to represent the phylogenetic distances.

Python

Software Architecture

Machine Learning (ML)

Java

Software Testing

Project ID: 38838862

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4 proposals

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Active 1 yr ago

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4 freelancers are bidding on average $40 CAD for this job

@malkesh3m

⭐ Hi, My availability is immediate. I read your project post on Python Developer with a strong understanding of phylogenetics. We are experienced full-stack Python developers with skill sets in - Python, Django, Flask, FastAPI, Jupyter Notebook, Selenium, Data Visualization, ETL - React, JavaScript, jQuery, TypeScript, NextJS, React Native - NodeJS, ExpressJS - Web App Development, Data Science, Web/API Scrapping - API Development, Authentication, Authorization - SQLAlchemy, PostegresDB, MySQL, SQLite, SQLServer, Datasets - Web hosting, Docker, Azure, AWS, GPC, Digital Ocean, GoDaddy, Web Hosting - Python Libraries: NumPy, pandas, scikit-learn, tensorflow, etc. Please send a message So we can quickly discuss your project and proceed further. I am looking forward to hearing from you. Thanks

$89 CAD in 1 day

4.3

(17 reviews)

4.3

@nailas2

Hello, I'm an experienced Python developer with expertise in phylogenetic analysis. I can implement Jukes-Cantor, Kimura 2-parameter, and Tamura-Nei distances, work with Phylip data format, and create detailed visualizations using libraries like Biopython. Let’s discuss how I can help with your project! Best regards, Naila shehzadi

$20 CAD in 5 days

0.0

(0 reviews)

0.0

@junaidhussnain36

Solution to your project based on my expertise: - Implement the Jukes-Cantor, Kimura 2-parameter, and Tamura-Nei distance methods in Python. - Use the Phylip data format for input processing. - Create visualizations of phylogenetic distances using libraries like Matplotlib or Seaborn. Hi, Junaid here, Software Engineer, I can help you with this project. From your requirements, I understand that you need to implement specific phylogenetic distance methods and generate corresponding visualizations. I have a few questions to get more clarity: - Do you have a specific dataset in Phylip format ready, or would you like assistance in preparing one? - Are you looking for a particular type of visualization (e.g., heatmaps, dendrograms)? - Do you need the distance computations to be optimized for large datasets? Let's have a quick chat or call, to discuss things in detail.

$30 CAD in 7 days

0.0

(0 reviews)

0.0

@asmaah45

I am excited to assist you with implementing the specified phylogenetic distance methods: Jukes-Cantor, Kimura 2-parameter, and Tamura-Nei. My expertise in Python programming, coupled with a strong understanding of phylogenetics and data visualization, makes me a great fit for this project. Implementation of Distance Methods: Develop Python functions to calculate Jukes-Cantor, Kimura 2-parameter, and Tamura-Nei distances. Ensure accurate handling of the Phylip data format for input sequences. Phylogenetic Tree Creation: Use libraries like Biopython and DendroPy to compute phylogenetic distances and generate trees. Ensure compatibility with the computed distance matrices. Visualizations: Create annotated, detailed phylogenetic trees using visualization tools such as matplotlib, seaborn, or specialized libraries like ete3. Provide clear and visually appealing representations of the computed distances. Documentation: Comprehensive comments and documentation for the Python code. An accompanying report or README detailing the methodology, implementation, and usage instructions.

$20 CAD in 5 days