A Numerical computing library for handling large, multi-dimensional arrays and mathematical functions.
Scientific computing library that builds on NumPy and provides a wide range of numerical algorithms and statistical functions.
Data analysis and manipulation library, commonly used for handling and analyzing structured data.
Plotting library for creating visualizations, including charts, histograms, and 2D/3D plots.
Statistical data visualization library that works well with Pandas and provides additional plotting options.
Machine learning library with a variety of algorithms for classification, regression, clustering, and more.
Open-source machine learning framework for building and training neural networks.
High-level neural networks API, often used in conjunction with TensorFlow for rapid prototyping and deep learning.
Deep learning library with a dynamic computational graph that enables efficient training and deployment of neural networks.
Computer vision library with a wide range of functions for image and video processing, including object detection and tracking.
Collection of tools for biological computation, including parsing sequence data, performing sequence alignments, and accessing biological databases.
Library for natural language processing tasks, such as tokenization, stemming, and part-of-speech tagging.
Image processing and analysis library widely used in bioimage informatics and microscopy.
Library for medical image analysis, segmentation, and registration tasks.
Library for reading, writing, and working with DICOM (Digital Imaging and Communications in Medicine) files used in medical imaging.
Library for reading and writing neuroimaging file formats, including NIfTI and Analyze.
Medical image processing library that provides functions for image preprocessing, segmentation, and evaluation.
Library for extracting radiomics features from medical images, commonly used in radiology research.
Library for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks. Often used for analyzing biological networks and pathways.
Library for implementing and running evolutionary algorithms, which can be applied to various bioinformatics and optimization problems.
A collection of R packages and workflows for analyzing and interpreting genomic data, including gene expression analysis, DNA sequencing, and more. While not a Python library, it's commonly used in biological research.
Part of the Biopython library, SeqIO provides a simple interface for reading and writing sequence files in various formats, such as FASTA, GenBank, and Swiss-Prot.
Molecular visualization system used for displaying and analyzing 3D molecular structures. It has a Python API for scripting custom analyses and visualizations.
Library for symbolic mathematics, often used for mathematical modeling and simulation in biological and biomedical engineering applications.
Library for molecular dynamics simulations, particularly focused on simulating proteins and biomolecules at atomic detail.
Probabilistic programming library for Bayesian modeling and inference, commonly used in computational biology and biostatistics.
Library that provides a wide range of statistical models and tests, including regression analysis, time series analysis, and hypothesis testing.
There are specialized toolkits available for specific tasks in bioinformatics, such as Biopython's Phylo for phylogenetics, Biopython's Seq for sequence manipulation, and PyMOL's API for molecular modeling and visualization.
Library for manipulating and analyzing genomic data, including sequence alignment, variant calling, and genome annotation.
Genetic Algorithm library for solving optimization problems, which can be applied to various biomedical and bioengineering tasks.
Library for image analysis in high-throughput microscopy, commonly used in cell biology and drug discovery research.
Deep learning library specifically designed for drug discovery and chemistry-related tasks, including molecular property prediction and drug design.
Part of the Biopython library, Entrez provides access to the NCBI (National Center for Biotechnology Information) databases, allowing retrieval of biological data and metadata.
Library for 3D computer graphics, image processing, and visualization, often used in medical imaging applications.
Open-source cheminformatics library for working with chemical structures and molecules, including molecular fingerprinting, substructure searching, and similarity analysis.
Interactive plotting library that allows the creation of interactive and customizable visualizations, including charts, maps, and dashboards.
Library for biosignal processing and analysis, specifically focused on neurophysiological and physiological data, such as electroencephalography (EEG) and heart rate variability (HRV).
Library for brain imaging analysis, including functional MRI (fMRI) and diffusion tensor imaging (DTI), commonly used in neuroscience research.
Library for storing and retrieving biological data in relational databases, providing a convenient interface for managing large-scale biological databases.
Library for computing various molecular descriptors and fingerprints for drug design and bioinformatics analysis.
Library for analyzing neurophysiological data, such as electroencephalography (EEG) and magnetoencephalography (MEG).
Low-code machine learning library that automates the end-to-end machine learning workflow, making it easier to develop predictive models in biomedical research.
Library for analyzing patterns of brain activity in functional neuroimaging data, commonly used in neuroimaging and cognitive neuroscience research.
Library for building neuroimaging pipelines, allowing the integration of multiple neuroimaging software packages for streamlined processing and analysis.
Library that integrates the Plotly library with Pandas for creating interactive and visually appealing statistical visualizations.
Library for materials analysis and characterization, including crystallography, electronic structure analysis, and materials property prediction.
Library for Bayesian statistical modeling and inference, useful for analyzing complex biological and clinical data.
Library for statistical learning and analysis of neuroimaging data, providing a range of machine learning and pattern recognition algorithms.
Library for reading, writing, and working with VCF (Variant Call Format) files commonly used in genomic analysis.
Part of the Bioconductor project, this library provides classes and methods for representing and manipulating genomic intervals and ranges.
Library for geometric deep learning on graphs and meshes, useful for analyzing biological networks and molecular structures.
Part of the Biopython library, AlignIO allows reading and writing of sequence alignments in various formats, such as FASTA and Clustal.
Library for evaluating medical image segmentation and registration algorithms, providing various metrics such as Dice similarity coefficient and Hausdorff distance.
Library for working with Graphviz graph visualization software, enabling the creation and rendering of complex graphs and networks.
Library for creating 2D vector graphics, commonly used for generating publication-quality figures in scientific and medical research.
Library for large-scale network analysis, offering a wide range of algorithms for centrality, community detection, and network visualization.
Library for image processing and computer vision tasks, providing functions for filtering, segmentation, feature extraction, and more.
Library for building and simulating spiking neural networks, useful for studying computational neuroscience and neural engineering.
Library for analyzing and visualizing dynamic atomic probe (DAP) data, which is used for studying nanoscale properties of materials.
Data mining and machine learning library with a visual programming interface, useful for exploratory analysis and predictive modeling in biomedical research.
Library for graph neural networks (GNNs), specifically designed for deep learning on graphs and networks, applicable to biological network analysis.
Library for probabilistic modeling and analysis, particularly useful for modeling biological systems and analyzing genetic data.
Quantum Toolbox in Python, designed for simulating open quantum systems and performing quantum computing simulations in the field of biophysics.
Library for modeling and simulating biochemical reaction networks, commonly used in systems biology research.
Library for analyzing biological networks, offering various algorithms for network visualization, clustering, and topological analysis.
Probabilistic programming library that supports various Bayesian models, allowing inference and parameter estimation in biomedical research.
Library for accessing biological databases and web services, facilitating programmatic access to a wide range of biological data sources.
Lightweight PyTorch wrapper that simplifies the training and deployment of machine learning models, including those in the medical and biological domains.
Python library for accessing ChEMBL, a large database of bioactive molecules and their properties, facilitating drug discovery research.
Library for analyzing and visualizing multi-dimensional and multi-modal neuroimaging data, commonly used in neurophysiology research.
Library for converting and organizing neuroimaging data in the Brain Imaging Data Structure (BIDS) format, ensuring compatibility and reproducibility.
Library for reading and writing biological file formats, including microscopy images, facilitating interoperability across various imaging systems.
Library for measuring image quality, providing metrics for assessing image sharpness, noise, contrast, and distortion.
A collection of measures and metrics for image quality assessment. PIQ helps you to concentrate on your experiments without the boilerplate code.
Library for graph analysis and modeling, offering efficient algorithms for network analysis, community detection, and graph visualization.
Library for performing astronomical calculations and analysis, offering tools for time series analysis, period finding, and data visualization.
Python interface for the Rosetta software suite, used for protein structure prediction, protein design, and molecular docking.
Library for bioinformatics analysis, providing functionalities for sequence alignment, phylogenetic analysis, and microbial ecology.
Library for mining frequent sequential patterns in biological and biomedical data, useful for discovering temporal relationships in sequential data.
Library for analyzing and visualizing neuroimaging data, particularly focused on magnetoencephalography (MEG) and electroencephalography (EEG).
Library for predicting gene functions and interactions using deep learning techniques, facilitating functional genomics research.
Library for hyperspectral image analysis, offering tools for spectral unmixing, classification, and visualization in remote sensing and biological imaging.
Library for image analysis and machine learning, providing algorithms for image segmentation, feature extraction, and object recognition.
Library for handling the BioC format, which is commonly used for sharing text mining results and annotations in biomedical literature.
Library for analyzing clinical neuroimaging data, focusing on the reproducible processing and analysis of MRI and PET data in clinical studies.
Library for spatial data analysis, providing tools for point pattern analysis, spatial clustering, and spatial interpolation in biology and ecology.
Library for building and executing complex data processing pipelines, often used in bioimaging and neuroimaging studies.
Library for parsing, manipulating, and working with Variant Call Format (VCF) files, commonly used in genomic data analysis.
Library for exploring and analyzing genetic variation data, offering tools for genotype calling, haplotype phasing, and population genetics analysis.
Library for contouring and visualizing gridded data, useful for creating 2D and 3D visualizations of biomedical imaging data.
Library for deep learning-based analysis and reconstruction of magnetic resonance imaging (MRI) data, useful for image denoising, super-resolution, and reconstruction tasks.
Library for survival analysis, offering tools for analyzing time-to-event data and building survival models in biomedical research.
Library for harmonizing and integrating multi-site neuroimaging data, facilitating the removal of site-specific variability in large-scale studies.
Library for applying graph neural networks to biological and biomedical problems, enabling graph-based representation learning and prediction tasks.
Library for clustering and analyzing spatially resolved transcriptomics data, providing tools for spatial transcriptomics analysis and visualization.
Library for analyzing morphological properties of objects in images, particularly useful for biological and biomedical image analysis.
Library for molecular docking and virtual screening, facilitating the exploration of protein-ligand interactions for drug discovery and design.
Library for X-ray fluorescence analysis and imaging, providing tools for data analysis, quantification, and visualization in XRF spectroscopy.
Library for accessing and analyzing data from the Allen Brain Atlas, a comprehensive collection of gene expression and neuroanatomical data.
Library for single-cell RNA sequencing (scRNA-seq) analysis, offering tools for preprocessing, clustering, and visualization of scRNA-seq data.
Library for analyzing hydrogen-deuterium exchange mass spectrometry (HDX-MS) data, enabling the study of protein structure, dynamics, and interactions.
Interface to the Abaqus finite element analysis software, allowing automation and customization of simulations in biomedical engineering and biomechanics.
Library for accessing and analyzing financial, economic, and alternative data, providing datasets that can be relevant for biomedical and healthcare research.
Library for ensemble clustering, offering tools for combining multiple clustering algorithms to improve clustering results in biological and biomedical data analysis.
Library for model interpretability and explaining individual predictions, useful for understanding the impact of features in biomedical models.
Library for color deconvolution and analysis of histological stains, facilitating automated quantification and classification of tissue samples.
A library built on spaCy specifically designed for biomedical text processing. It provides domain-specific tokenization, named entity recognition (NER), and entity linking capabilities tailored to medical and clinical text.
A biomedical concept annotation tool that utilizes deep learning techniques for automated entity recognition and linking. It offers pre-trained models for various biomedical domains and allows customization for specific tasks.
A library that applies BERT-based models to clinical text analysis. It provides pre-trained models for tasks like named entity recognition, relation extraction, and question answering in the medical domain.
A widely-used natural language processing system specifically developed for clinical text processing. It offers tools for various NLP tasks, including sentence parsing, named entity recognition, and relation extraction in clinical narratives.
A tool developed by the National Library of Medicine (NLM) for mapping biomedical text to concepts in the Unified Medical Language System (UMLS). It enables automated concept recognition and semantic annotation of medical text.
An application programming interface (API) that allows programmatic access to the cBioPortal platform. It facilitates querying and retrieving genetic and clinical data from cancer studies, supporting research and analysis in cancer genomics.
A gene name normalization tool that maps gene mentions in text to standardized identifiers, aiding in the identification and linking of gene-related information in biomedical literature.
A text mining tool specifically designed for identifying genetic variant mentions in biomedical text. It helps in the extraction of variant-gene-disease relationships from scientific literature.
A library for semantic annotation of electronic health records (EHRs) using biomedical ontologies. It enables the mapping of EHR data to standard terminologies and supports data interoperability and analysis.
A library for clinical text processing that focuses on context-aware negation detection. It provides tools for identifying negated concepts and determining the scope and extent of negation in clinical narratives.
A named entity recognition system specifically designed for biomedical text. It uses conditional random fields (CRFs) to identify and classify biomedical entity mentions.
A library for contextual analysis of clinical text. It focuses on extracting and annotating medical concepts and their attributes, such as negation, uncertainty, and family history, to facilitate information extraction.
A rule-based sentence segmentation library for biomedical text. It provides customizable rules for splitting text into sentences, considering domain-specific requirements and patterns.
A semantic interpreter for biomedical text that extracts semantic predications from text using UMLS concepts and relations. It enables the extraction of biomedical knowledge and relationships from scientific literature.
A variant of BERT (Bidirectional Encoder Representations from Transformers) that is specifically pretrained on biomedical text. It can be fine-tuned for various biomedical NLP tasks, such as named entity recognition and relation extraction.
A tool for training custom medical concept recognition models. It allows users to create labeled datasets, train domain-specific models using spaCy, and integrate them with other NLP pipelines.
A collection of NLP tools for biomedical text processing. It includes modules for sentence splitting, tokenization, part-of-speech tagging, dependency parsing, and more.
A named entity recognition tool specifically designed for biomedical text. It identifies and classifies entities such as genes, proteins, and cell types.
A dataset and library for natural language inference in the medical domain. It provides labeled sentence pairs for training and evaluating models on tasks like textual entailment and inference.
A high-performance Python Radiology Text Analysis System.
A collaborative framework for annotating medical datasets.