biopython | Official git repository for Biopython | Genomics library

 by   biopython Python Version: 1.83 License: Non-SPDX

kandi X-RAY | biopython Summary

kandi X-RAY | biopython Summary

biopython is a Python library typically used in Healthcare, Pharma, Life Sciences, Artificial Intelligence, Genomics applications. biopython has no bugs, it has no vulnerabilities, it has build file available and it has medium support. However biopython has a Non-SPDX License. You can install using 'pip install biopython' or download it from GitHub, PyPI.

Official git repository for Biopython (originally converted from CVS)

            kandi-support Support

              biopython has a medium active ecosystem.
              It has 3633 star(s) with 1625 fork(s). There are 167 watchers for this library.
              There were 2 major release(s) in the last 6 months.
              There are 428 open issues and 1101 have been closed. On average issues are closed in 171 days. There are 113 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of biopython is 1.83

            kandi-Quality Quality

              biopython has 0 bugs and 0 code smells.

            kandi-Security Security

              biopython has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              biopython code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              biopython has a Non-SPDX License.
              Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

            kandi-Reuse Reuse

              biopython releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              biopython saves you 938874 person hours of effort in developing the same functionality from scratch.
              It has 468102 lines of code, 8425 functions and 740 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed biopython and discovered the below as its top functions. This is intended to give you an instant insight into biopython implemented functionality, and help decide if they suit your requirements.
            • Read a PIC file .
            • Return the radius of an atom .
            • Fetch the internal id list from the database .
            • Returns an iterator over the FASTQ - M10 records .
            • Draw a cross link .
            • Parse coordinates .
            • Writes a SCAD file to fp .
            • r Compute the DNA sequence .
            • Run a qblast query .
            • Read a PFM file .
            Get all kandi verified functions for this library.

            biopython Key Features

            No Key Features are available at this moment for biopython.

            biopython Examples and Code Snippets

            biopython-coronavirus,Running the Notebook locally
            Jupyter Notebookdot img1Lines of Code : 6dot img1License : Permissive (MIT)
            copy iconCopy
            git clone;
            cd biopython-coronavirus
            pip3 install jupyter biopython
            conda env create -f environment.yml
            conda activate biopython-coronavirus
            jupyter-notebook biopython-coronavirus-notebook.ipynb
            find a Pattern Match in string in Python
            Pythondot img2Lines of Code : 7dot img2License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import re
            re.findall(r"B[^P]C|M[^P]D", string)
            ['BAC', 'MLD']
            editing python script file again and again
            Pythondot img3Lines of Code : 17dot img3License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            AA_seq=input("write Amino Acid Sequence:" )
            value={"V": 3.1,"Y":3.5,"W":4.7,"T" :5.3,"S":5.1,"P":3.7,
            Loop through every file with specific format in a directory using sys argv
            Pythondot img4Lines of Code : 9dot img4License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            with open(glob_path, "rU") as input_fq:
            with open(file_path, "rU") as input_fq:
            glob_path = path.glob('*.fastq')
            for file_path in glob_path:
                with open(file_path, "rU") as input_fq:
            How to renumber residues (start from 1 in continuation among chains) in pdb file in python?
            Pythondot img5Lines of Code : 180dot img5License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            ATOM     25  N   ALA E   5      48.087  97.950  74.514  1.00  9.33           N  
            ATOM     26  CA  ALA E   5      48.052  99.292  73.904  1.00  9.37           C  
            ATOM     27  C   ALA E   5      47.483 100.285  74.935  1.00  9.65           
            copy iconCopy
            seqtk subseq   > out.fa
            unique clones finding using SeqIO module of biopython
            Pythondot img7Lines of Code : 11dot img7License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            seen_records = set()
            records_to_keep = []
            for record in SeqIO.parse('DNA_library', 'fasta'):
              seq = str(record.seq)
              if seq not in seen_records:
            Variables not being reassigned in Loop
            Pythondot img8Lines of Code : 32dot img8License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            import itertools
            import re
            degen = {"A": 4,"R": 6,"N": 2,"D": 2,"C": 2, "E": 2,"Q": 2,"G": 2,"H": 2,"I": 3, "L": 6,"K": 2,"M": 1,"F": 2,"P": 4, "S": 6,"T": 4,"W": 1, "Y": 2, "V": 4}
            d= {'A': ['GCA', 'GCC', 'GCG', 'GCT'], 'C': ['TGC', 'TGT
            translate DNA sequences to protein sequences within a pandas dataframe
            Pythondot img9Lines of Code : 2dot img9License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            df['protein'] = df['DNA'].apply(lambda x: Seq(x).translate(), axis=1)
            Python def invalid syntax
            Pythondot img10Lines of Code : 17dot img10License : Strong Copyleft (CC BY-SA 4.0)
            copy iconCopy
            print('Total proteins:', len(df))
            def conv(item):
                return len(item)
            def to_str(item):
                return str(item)
            df['sequence_str'] = df[0].apply(to_str)
            df['length'] = df[0].apply(conv)
            df.rename(columns={0: "sequence"}, 

            Community Discussions


            Error "no free space in /var/cache/apt/archives" in singularity container, but disk not full
            Asked 2022-Apr-14 at 10:20

            I'm trying to reproduce results of an older research paper and need tp run a singularity container with nvidia CUDA 9.0 and torch 1.2.0. Locally I have Ubuntu 20.04 as VM where I run singularity build. I follow the guide to installing older CUDA versions. This is the recipe file



            Answered 2022-Apr-14 at 10:20

            As described in overview section of singularity build documentation

            build can produce containers in two different formats that can be specified as follows.

            • compressed read-only Singularity Image File (SIF) format suitable for production (default)
            • writable (ch)root directory called a sandbox for interactive development (--sandbox option)

            Adding --sandbox should make the system files writable which should resolve your issue.

            Ideally, I'd suggest adding any apt-get install commands to the %post section in your recipe file.



            find a Pattern Match in string in Python
            Asked 2022-Mar-30 at 09:43

            I am trying to find a amino acid pattern (B-C or M-D, where '-' could be any alphabet other than 'P') in a protein sequence let say 'VATLDSCBACSKVNDNVKNKVKVKNVKMLDHHHV'. Protein sequence in in a fasta file.

            I have tried a lot but couldn't find any solution.

            I tried a lot. the following code is one of them



            Answered 2022-Mar-30 at 09:43

            In python you can use the Regex module (re):



            Loop through every file with specific format in a directory using sys argv
            Asked 2022-Mar-22 at 16:04

            I'd like to loop through every file in a directory given by the user and apply a specific transformation for every file that ends with ".fastq".

            Basically this would be the pipeline:

            1. User puts the directory of where those files are (in command line)
            2. Script loops through every file that has the format ".fastq" and applies specific transformation
            3. Script saves new output in ".fasta" format

            This is what I have (python and biopython):



            Answered 2022-Mar-22 at 15:55

            Your problem is with this line:



            How to replace characters at specific positions from a file list?
            Asked 2022-Mar-14 at 16:50

            I have a file containing a sequence:



            Answered 2022-Mar-14 at 15:14

            Using awk with empty FS. This may not work with every awk version or with arbitrarily long sequences:



            Get consensus from a MSA fasta file with IUPAC ambiguities in Python
            Asked 2022-Mar-08 at 21:32

            I have an almost similar question to the topic :

            I have a fasta file with align sequence and I want to generate a consensus by using IUPAC code.

            So far I wrote :



            Answered 2022-Mar-08 at 21:32

            The raw solving. Although, Biopython code on GitHub looks not better. You can extend this for your aims.



            I have a fasta file with millions of sequences. I want to only extract those that's names match within a .txt file, how can I go about doing this?
            Asked 2022-Mar-08 at 11:29

            I have been sorting through a ~1.5m read fasta file ('V1_6D_contigs_5kbp.fa') to determine which of the reads are likely to be 'viral' in origin. The reads in this file are denoted as Vx_Cz - where x is 1-6, depending on which trial group it came from, and z is the contig number/name from 1-~1.5m. e.g V1_C10810 or V3_C587937...

            Through varying bioinformatic pipelines I have produced a .txt file with a list (2699 long) of the contig names that are predicted (<0.05) to be viral. I now need to use this list of predicted contigs to extract and produce a new fasta file that contains only these contigs.

            The theoretical idea behind my code is that it opens the .txt file (names of each significant contig) and the original fasta file, goes through each line of the .txt file and sets the line (contig name) as a variable. It should then loop through the original fasta file which contains all the sequence information and if the contig name matches the (contig name from original file) it should then export the full record information to a new file.

            I think I am close, but my current iterations seems to run only one or the the other loop as I expect them to.

            Please see the code below. I have added notes below to what runs wrong with each program I have tried.

            I am using Python, including SeqIO the Biopython application.



            Answered 2022-Mar-08 at 09:43

            Among quite a few typos, the main issue is that the line from lines=f.readlines() will still contain the newline character \n and will therefore never match the id from SeqIO, the solution is to use a simple strip() call:



            unique clones finding using SeqIO module of biopython
            Asked 2022-Mar-06 at 19:39

            I am working on Next Generation Sequencing (NGS) analysis of DNA. I am using SeqIO Biopython module to parse the DNA libraries in Fasta format. I want to filter the unique clones (unique records) only. I am using the following python code for this purpose.



            Answered 2022-Mar-06 at 15:24

            I don't have your files so I cannot test the actual performance gain you'll get, but here are some things that stick out as slow to me:

            • the line records=list(SeqIO.parse('DNA_library', 'fasta')) converts the records into a list of records, which may sound inoffensive but becomes costly if you have millions of records. According to the docs, SeqIO.parse(...) returns an iterator so you can simply iterate over it directly.
            • Use a set instead of a list when keeping track of seen records. When performing membership checking using in, lists must iterate through every element while sets perform the operation in constant time (more info here).

            With those changes, your code becomes:



            translate DNA sequences to protein sequences within a pandas dataframe
            Asked 2022-Feb-17 at 18:01

            I have a pandas dataframe that contains DNA sequences and gene names. I want to translate the DNA sequences into protein sequences, and store the protein sequences in a new column.

            The data frame looks like:

            DNA gene_name ATGGATAAG gene_1 ATGCAGGAT gene_2

            After translating and storing the DNA, the dataframe would look like:

            DNA gene_name protein ATGGATAAG... gene_1 MDK... ATGCAGGAT... gene_2 MQD...

            I am aware of biopython's ( ability to translate DNA to protein, for example:



            Answered 2022-Feb-17 at 17:57

            Since you want to translate each sequence in the "DNA" column, you could use a list comprehension:



            Joblib too slow using "if not in" loop
            Asked 2022-Jan-01 at 10:04

            I am working with amino acid sequences using the Biopython parser, but regardless of data format (the format is fasta, that is, you can imagine them as strings of letters as follows preceded by the id), my problem is that I have a huge amount of data and despite having tried to parallelize with joblib the estimate of the hours it would take me to run this simple code is 400.

            Basically I have a file that contains a series of ids that I have to remove (ids_to_drop) from the original dataset (original_dataset), to create a new file (new_dataset) that contains all the ids contained in the original dataset without the ids_to_drop.

            I've tried them all but I don't know how else to do it and I'm stuck right now. Thanks so much!



            Answered 2021-Dec-31 at 18:43

            This looks like a simple file filter operation. Turn the ids to remove into a set one time, and then just read/filter/write the original dataset. Sets are optimized for fast lookup. This operation will be I/O bound and would not benefit from parallelization.



            Why does the 'join' method for Seq object in Biopython not work on the last element of a list?
            Asked 2021-Dec-19 at 16:40

            The code below is from the Biopython tutorial. I intend to add 'N5' after every contig. Why is the trailing N10 not present after the third contig "TTGCA"?



            Answered 2021-Dec-19 at 16:40

            This has nothing to do with biopython.

            This is just how string.join works:


            Community Discussions, Code Snippets contain sources that include Stack Exchange Network


            No vulnerabilities reported

            Install biopython

            You can install using 'pip install biopython' or download it from GitHub, PyPI.
            You can use biopython like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.


            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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