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The Biopython project is an open-source collection of non-commercial Python tools for computational biology and bioinformatics, created by an international association of developers. [ 1 ] [ 4 ] [ 5 ] It contains classes to represent biological sequences and sequence annotations , and it is able to read and write to a variety of file formats.
Open Bioinformatics Foundation: Biopython: Python language toolkit Cross-platform: Biopython [2] Open Bioinformatics Foundation: BioRuby: Ruby language toolkit Linux, macOS, Windows [3] GPL v2 or Ruby: Open Bioinformatics Foundation: BLAST: Algorithm and program for comparing primary biological sequence information, including DNA and protein ...
Python tool for modeling and analyzing SBML models [21] [22] [23] multiplatform (Python) BSD-3: Yes pySB: Python-based [24] platform with specialization in rule-based models. multiplatform (Python) BSD-3: Partial ReaDDy: Particle-based spatial simulator with intermolecular potentials [25] Linux and Mac: Custom: Not applicable SBSCL
fastqp Simple FASTQ quality assessment using Python. Kraken: [9] A set of tools for quality control and analysis of high-throughput sequence data. HTSeq [10] The Python script htseq-qa takes a file with sequencing reads (either raw or aligned reads) and produces a PDF file with useful plots to assess the technical quality of a run.
Galaxy [2] is an open-source scientific workflow system designed to make research accessible, reproducible, and transparent. Originally developed for computational biology, Galaxy has evolved into a domain-agnostic framework utilized across various scientific disciplines.
Orange, a data mining, machine learning, and bioinformatics software; Pandas – High-performance computing (HPC) data structures and data analysis tools for Python in Python and Cython (statsmodels, scikit-learn) Perl Data Language – Scientific computing with Perl; Ploticus – software for generating a variety of graphs from raw data
samtools view -h -b sample_sorted.bam "chr1:10-13" > tiny_sorted.bam Extract the same reads as above, but instead of displaying them, writes them to a new bam file, tiny_sorted.bam . The -b option makes the output compressed and the -h option causes the SAM headers to be output also.
Examples of BioNumerics applications are whole genome Multi Locus Sequence Typing (wgMLST), whole genome Single Nucleotide Polymorphisms (wgSNP), genome comparison, identification based on MALDI-TOF Mass Spectrometry, PFGE typing, Amplified Fragment Length Polymorphism (AFLP) typing, sequence-based typing of viruses, antibiotic resistance ...