Open Source Molecular Science Software
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Molecular Science Software
View 2313 business solutionsBrowse free open source Molecular Science software and projects below. Use the toggles on the left to filter open source Molecular Science software by OS, license, language, programming language, and project status.
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Avogadro
An intuitive molecular editor and visualization tool
Avogadro is an advanced molecular editor designed for cross-platform use in computational chemistry, molecular modeling, bioinformatics, materials science and related areas. It offers a flexible rendering framework and a powerful plugin architecture. -
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Bowtie, an ultrafast, memory-efficient short read aligner for short DNA sequences (reads) from next-gen sequencers. Please cite: Langmead B, et al. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10:R25.
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PyRx - Virtual Screening Tool
Virtual Screening software for Computational Drug Discovery
PyRx is a Virtual Screening software for Computational Drug Discovery that can be used to screen libraries of compounds against potential drug targets. PyRx enables Medicinal Chemists to run Virtual Screening from any platform and helps users in every step of this process - from data preparation to job submission and analysis of the results. While it is true that there is no magic button in the drug discovery process, PyRx includes docking wizard with easy-to-use user interface which makes it a valuable tool for Computer-Aided Drug Design. PyRx also includes chemical spreadsheet-like functionality and powerful visualization engine that are essential for Rational Drug Design. Please visits PyRx home page to learn more about PyRx and watch videos on how to use it. -
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Toxtree: Toxic Hazard Estimation
Toxicity prediction for chemical compounds
A GUI application which estimates toxic hazard of chemical compounds. The latest version includes the following toxicity prediction modules: -Cramer rules (oral toxicity) -Toxicity mode of action via Verhaar scheme -Skin irritation and Eye irritation prediction -Benigni / Bossa rulebase for mutagenicity and carcinogenicity prediction -START biodegradation and persistence prediction -Skin sensitisation reactivity domain -Kroes TTC Decision tree -SMARTCyp - Cytochrome P450-Mediated Drug Metabolism and metabolites prediction -Structure Alerts for the in vivo micronucleus assay in rodents (ISSMIC) -Structural Alerts for Functional Group Identification (ISSFUNC) -Structural alerts associated with covalent protein binding and DNA binding. - Ames mutagenicity Toxtree provides a plugin framework to incorporate different approaches to the estimation. Platform independent (written in Java), with the use of The Chemistry Development Kit. -
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OpenCFU
An application to count bacterial colonies and other circular objects
OpenCFU is a completely open source lightweight application designed to enumerate clustered circular objects such as bacterial colonies. It can handle digital pictures as well as live stream from a video device/webcam. OpenCFU is cross-platform, fast, reliable and allows the user to implement intuitive filters. Additional information is provided on the website: http://opencfu.sourceforge.net/ OpenCFU is published on PLoS ONE: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0054072 -
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Subread
High-performance read alignment, quantification and mutation discovery
The Subread software package is a tool kit for processing next-gen sequencing data. It includes Subread aligner, Subjunc exon-exon junction detector and featureCounts read summarization program. Subread aligner can be used to align both gDNA-seq and RNA-seq reads. Subjunc aligner was specified designed for the detection of exon-exon junction. For the mapping of RNA-seq reads, Subread performs local alignments and Subjunc performs global alignments. Subread and Subjunc were published in the following paper: Yang Liao, Gordon K Smyth and Wei Shi. "The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote", Nucleic Acids Research, 2013, 41(10):e108 -
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Gabedit is a Graphical User Interface for FireFly (PC-Gamess), Gamess-US, Gaussian, Molcas, Molpro, MPQC, NWChem, OpenMopac, Orca, PSI4 and Q-Chem computational chemistry packages.
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Molsketch
2D molecule editor
Molsketch is a 2D molecular editing tool. Its goal is to help you draw molecules quick and easily. Of course you're creation can be exported afterwards in high quality in a number of vector and bitmap formats. -
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RasTop is a molecular graphics program intended for the visualisation of proteins, nucleic acids and small molecules based on the popular Rasmol software. The program is aimed at the rapid visualization and analysis of molecules.
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EMC: Enhanced Monte Carlo; A multi-purpose modular and easy extendable solution to molecular and mesoscale simulations
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MzDOCK - Multiple Ligand Docking Tool
MzDOCK is A Virtual Screening Tool For Drug Discovery Research
- Molecular Docking Virtual Screening Tool To Aid In Drug Discovery Research. - Developed with Synchronized functioning of Python and Batch scripts - Compatible on Windows - Accepted on Journal of Computational Chemistry - DOI: 10.1002/jcc.27390 -Integerated With Pymol-open-source for visualizing interaction (PSE file) generated from MzDOCK - Integrated with Molecule Drawing Tool - JSME Editor - If you are facing any issues or for queries . Contact us - kabeermuzammil614@gmail.com MzDOCK Development -
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picard
A set of tools for working with high-throughput sequencing data
A set of tools (in Java) for working with next generation sequencing data in the SAM/BAM format. Note that development has moved to GitHub at https://github.com/broadinstitute/picard and support is available on the GATK forum at http://gatkforums.broadinstitute.org/categories/ask-the-team -
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The SourceForge OpenRasMol project is an adjunct to the RasMol and OpenrasMol project at http://rasmol.org. It is hoped that the SourceForge OpenRasMol project will provide a convenient focal point for active collaborative contributions.
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Chemical structure sketching tool, for use with various cheminformatics applications. Convenient to use and moderately sophisticated. Suitable for viewing, creating and editing MDL MOL files.
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kSNP
kSNP4 does SNP discovery and SNP annotation from whole genomes
kSNP4 identifies the pan-genome SNPs in a set of genome sequences, and estimates phylogenetic trees based upon those SNPs. SNP discovery is based on k-mer analysis, and requires no multiple sequence alignment or the selection of a reference genome, so kSNP4 can take 100's of microbial genomes as input. A SNP locus is defined by an oligo of length k surrounding a central SNP allele. kSNP4 can analyze both complete (finished) genomes and unfinished genomes in assembled contigs or raw, unassembled reads. Finished and unfinished genomes can be analyzed together, and kSNP can automatically download Genbank files of the finished genomes and incorporate the information in those files into the SNP annotation. No programming skills are required to use kSNP4 Gardner, S.N. and Hall, B.G. 2013. . PLoS ONE, 8(12):e81760.doi:10.1371/journal.pone.0081760 Gardner, S.N., T. Slezak, and B.G. Hall. 2015 Bioinformatics 31: 2877-2878 doi: 10.1093/bioinformatics/btv271 -
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BioXTAS RAW
Processing and analysis of Small Angle X-ray Scattering (SAXS) data.
BioXTAS RAW is a program for analysis of Small-Angle X-ray Scattering (SAXS) data. The software enables: creation of 1D scattering profiles from 2D detector images, standard data operations such as averaging and subtraction, analysis of radius of gyration (Rg) and molecular weight, and advanced analysis using GNOM and DAMMIF as well as electron density reconstructions using DENSS. It also allows easy processing of inline SEC-SAXS data and data deconvolution using the evolving factor analysis (EFA) or the regularized alternating least squares (REGALS) methods. Active source code is now maintained on github: https://github.com/jbhopkins/bioxtasraw To install: Check the instructions available at: http://bioxtas-raw.readthedocs.io/en/latest/install.html and in the Files tab. User guides: RAW guides are available at: http://bioxtas-raw.readthedocs.io/ and in the Files tab. To contact us, see: https://bioxtas-raw.readthedocs.io/en/latest/help.html -
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The Sashimi project hosts the Trans-Proteomic Pipeline (TPP), a mature suite of tools for mass-spec (MS, MS/MS) based proteomics: statistical validation, quantitation, visualization, and converters from raw MS data to the open mzML/mzXML formats.
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Ascalaph Designer
Graphic molecular dynamic package.
Molecular Graphics, Molecular Dynamics, Optimization, Quantum chemistry. Molecular model building. Explicit and implicit water models. http://www.biomolecular-modeling.com/Products.html -
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CAMPARI
Software for molecular simulations and trajectory analysis
We are proud to introduce version 5 of CAMPARI. We have added a number of new features, most notably a Python interface for interpreting user-supplied code (with the help of ForPy), a novel trajectory storage standard (with the help of libpqxx/PostgreSQL), and a module for performing transition path theory. Naturally, CAMPARI continues to provide the reference implementation of the ABSINTH force field paradigm and implicit solvation model. CAMPARI is a joint package for performing and analyzing molecular simulations, in particular of systems of biological relevance. It focuses on a wide availability of algorithms for (advanced) sampling and is capable of combining Monte Carlo and molecular dynamics in seamless fashion. CAMPARI offers the user a very high level of control over all implemented features. For more information and features, please refer to the project's homepage at http://campari.sourceforge.net/V5 -
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ShelXle
ShelXle is a Qt GUI for SHELXL
ShelXle combines an editor with syntax highlighting for the SHELXL-associated .ins (input) and .res (output) files with an interactive graphical display for visualization of a three-dimensional structure including the electron density (Fo) and difference density (Fo-Fc) maps. See J. Appl. Cryst. (2011). 44, 1281–1284. for details. -
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Our goal is to create an open source framework and toolset for modeling dynamic cellular network functions, and to develop a user community committed to using, extending and exploiting these tools to further our knowledge of biologic processes.
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GrowthRates
Calculate growth rates from microplate reader output
The Bellingham Research Institute (BRI) develops and distributes software that is free of charge to academic and other non-profit organizations. GrowthRates is our software tool that simplifies the analysis of microplate reader output from microbial growth experiments without having to program in Python, R, or MATLAB. It automates the calculation of growth rate parameters, including rates, lag times, maximum population density. Manual calculation of those parameters requires at least 5 minutes per well, or 32 hours for a 384 well plate. GrowthRates completely analyzes growth parameters in all 384 wells in under 5 minutes. CGR2 (Compare Growth Rates) is a statistical program specifically designed to assess the results of a growth rate experiment that has been analyzed using the program GrowthRates. The purpose of a statistical analysis is to establish our level of trust in both the data and in the conclusions we draw from that data. Both the GrowthRate and CGR2 packages are -
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luscus
molecular editor and viewer
Luscus is the program for graphical display and editing of molecular systems. The program allows fast and easy building and/or editing different molecular structures, up to several thousands of atoms large. Luscus can also visualize dipole moments, normal modes, molecular orbitals, electron densities and electrostatic potentials. In addition, simple geometrical objects can be rendered in order to point out a geometrical feature or a physical quantity. The program is developed as a graphical interface for MOLCAS program package, however it's adaptive nature makes possible using luscus with other computational program packages and chemical formats. If you use this program, please cite: G. Kovačević, V. Veryazov, J. Cheminformatics, 7 (2015) 1-10; DOI: 10.1186/s13321-015-0060-z -
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MZmine 2
A framework for differential analysis of mass spectrometry data
MZmine 2 is a framework written in Java for differential analysis of mass spectrometry data. -
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Web-based Electronic Laboratory Notebook (ELN) with integrated Chemical Inventory by the group of Prof. Goossen (TU Kaiserslautern, Germany), based on PHP/MySQL. Allows (sub-)structure search, reaction planning, management of spectra and literature.
Open Source Molecular Science Software Guide
Open source molecular science software is a type of software designed to work with molecules and chemical bonding in order to simulate and analyze various aspects of the chemistry. It can be used for many applications such as studying the physical properties of molecules, designing new pharmaceuticals or chemicals, developing materials with specific properties, and more. Open source molecular simulation software typically includes a number of different components that all need to be used together in order to provide complete simulations. This includes a modeling engine that handles the calculations involved in producing an accurate representation of the molecule or reaction being studied, as well as graphical user interfaces (GUIs) that allow users to interactively control the simulations and analyze results.
Many open source molecular science software packages are designed specifically for research use in academic settings. They often feature powerful scripting languages for creating automated procedures for tasks such as running multiple simulations at once and automating data analysis functions like plotting graphs or extracting parameters from large datasets. These scripting languages also allow experienced users to extend beyond what's available in standard packages by creating custom modules tailored specifically for their own unique needs. Additionally, some open source packages also come with access to development tools like compilers which enable developers interested in exploring more advanced features or making significant changes to any given package.
Finally, open source molecular simulation programs are built on top of established libraries such as Python SciPy or MATLAB Simulink that contain useful functions related to mathematical modeling and visualization techniques which can be leveraged when building new applications. Many packages have been designed in this way so that they can easily integrate with other programs written using these libraries, allowing scientists to quickly build complex systems combining existing components rather than having to develop each component from scratch every time they wish to explore something new.
Features of Open Source Molecular Science Software
- Simulation: Open source molecular science software provides tools for the simulation of molecules and chemical reactions. These simulations can help scientists understand the behavior of components at atomic or molecular level.
- Data Visualization: Molecular science software can be used to visualize data such as movie clips, three-dimensional images and plots. This allows researchers to better interpret their results, identify trends and make informed decisions.
- Data Analysis: Molecular science software provides tools to analyze data such as chemical energy calculations, structural analysis, quantum chemistry calculations and other numerical analyses that aid in understanding molecules structure.
- Modeling: Molecular science software also enables users to build models for a variety of contexts ranging from medicine to engineering design optimization. Such models enable users to represent physical processes more efficiently and accurately than traditional methods.
- Molecular Dynamics: This feature helps analyze movements between particles, allowing scientists to observe how systems interact over time and enable predictive modeling of those interactions through computation rather than relying on experimentation alone.
- Data Storage: Molecular science software also provides storage facilities for users to store and manage their data more efficiently. This allows researchers to access their results from different computers, networks and locations.
- Software Development Platforms: Open source molecular science software usually include libraries of scripts, modules and components that can be combined in various ways to develop custom programs for specific applications.
- Data Sharing: Many of these software packages provide tools to share and collaborate with other users, making it easier to share results, exchange ideas and collaborate on projects.
- Resource Management: Open source molecular science software provides tools to manage resources, such as by automating many tasks and allowing users to easily coordinate their efforts.
Types of Open Source Molecular Science Software
- Electronic Structure Software: This software simulates the behavior of atoms and molecules to calculate properties such as energies, atomic positions and forces. It is used for a variety of tasks including predicting chemical reaction rates, materials design and 3D printing.
- Molecular Dynamics Simulation Software: This type of software enables scientists to observe how a system evolves over time by using equations of motion that simulate the movement particles. It is often used to study protein folding pathways or other complex biological processes.
- Protein Structure Prediction Software: This type of software can predict a protein’s conformation (shape) given its amino acid sequence. It can also provide insight into the properties and functions of proteins related to their secondary structure or higher-level assemblies.
- Quantum Chemistry Software: This software uses quantum mechanical principles such as wave mechanics and energy minimization to calculate chemical properties such as bond lengths, atomic charges, dipole moments and vibrational spectra. The results are important for developing new drug compounds or understanding chemical reactions more precisely.
- Structural Biology Software: These programs help researchers visualize molecular structures from x-ray crystallography experiments or from simulated models built with electron density maps. They are an essential tool for gaining insight into the function, interactions and dynamics of proteins in biochemistry studies.
- Database Management Systems: These systems manage huge amounts data related to molecular sciences like publications, nucleotide sequences, mass spectral data, crystal structures etc.; allowing scientists access information quickly and efficiently when solving scientific problems.
- Image Analysis Software: This software allows researchers to extract useful information from their microscope images and videos. It can be used to quantify image intensities, distances, angles or other parameters difficult to measure by eye.
- Computational Chemistry Software: This type of software applies computational techniques to the study of chemical problems such as the synthesis of novel compounds, boiling points and crystal structures. It is an important tool for drug discovery and materials development.
- Spectroscopy Software: This software is used to analyze the spectra of compounds and identify them based on their unique spectral signatures. It can be used to understand the structure and behavior of a compound in more detail or to confirm the identity of an unknown material.
Open Source Molecular Science Software Advantages
- Cost Savings: Open source molecular science software offers users the ability to download and use the software for free, which can help save money in comparison to commercial software.
- Flexibility: Having access to an open source code allows users to customize the software according to their own needs or preferences. By making small tweaks or adding additional features, researchers are able to tailor the program to their specific requirements, allowing them more control over how they use the program.
- Sharing Resources: Open source applications provide a platform for researchers from all around the world who share a common interest and goals when it comes to studying molecules. With these platforms, scientists can easily upload data and share resources with one another efficiently and effectively.
- Collaboration: Thanks to open source molecular science software, collaboration is easier than ever before. Scientists can work together on a single project even if they’re located in different parts of the world. They’ll also have access shared resources from fellow research groups that may be beneficial for their project.
- Increased Accuracy: As more people contribute resources, accuracy is improved since everyone is working towards improving existing tools and developing new ones as well. This helps ensure that results obtained by using these programs are accurate and reliable compared with those gotten using conventional methods or commercial applications where only one or few developers are responsible for programming updates or improvements.
- Continuous Improvement: Open source molecular science software is open to constant improvement and feedback from the community. This makes it easier for developers to update and add new features as well as tools, making the program better with time.
Types of Users That Use Open Source Molecular Science Software
- Research Scientists: These are scientists who use open source software to analyze and interpret complex scientific data, such as genomic and proteomic information. They often work in laboratories or academic institutions.
- Bioinformaticians: These are computer specialists who specialize in analyzing huge amounts of biological data using open source programs. They develop algorithms, models and databases to interpret this data.
- Educators: Educators who use open source software can benefit from access to powerful tools that can be used for teaching purposes. Open source software also allows faculty and students alike to actively explore the capabilities of a range of code-based tools which allow them to understand complex biological systems more easily.
- Biomedical Engineers: Medical engineers that utilize open source software may include biomedical device designers, bioengineers, clinical engineers and others involved in developing medical technology for the healthcare industry.
- Health Professionals:Healthcare providers such as doctors, nurses, pharmacists and other healthcare practitioners rely on open source analysis tools to properly diagnose conditions or predict disease progression based on patient specific readings.
- Medical Companies & Pharmaceuticals: Companies within the pharmaceuticals industry set high standards when it comes to tests reliability, accuracy and ethical responsibility when running clinical trials with patients; which makes access to reliable open source software all the more important for them.
- Entrepreneurs & Startups: Many startups find themselves limited by expensive licenses or proprietary systems but since many molecular science platforms are now developed under an open license they’re able to take advantage of free resources while they build their business model around it.
- Industry Professionals & Regulatory Bodies: Businesses providing products or services within the biotechnology domain need reliable access to molecular science software applications in order to ensure compliance with any applicable regulations covering product manufacture or testing procedures. Government bodies may also take advantage of open source software to oversee and supervise industry activities.
How Much Does Open Source Molecular Science Software Cost?
Open source molecular science software is typically available for free. This type of software, which is often referred to as “free and open source,” are developed by a community of scientists and developers who share their work with the world for everyone to use. The only cost associated with this type of software is the time and effort it takes to download and learn how to use the program.
The benefit of using open source programs is that they can be easily customized or modified to do what you need them to do without having any access restrictions or licensing fees. They usually have comprehensive online help systems that provide detailed instructions on how to install and use the software, so there’s no need for extra training fees if you don’t already understand complex programming languages. In addition, these programs are regularly updated with new features and bug fixes, so you don't have to worry about purchasing a version upgrade just to get the latest features, all updates are completely free too.
Open source programs may offer basic functions like data analysis or manipulation, but there are also more advanced tools such as 3D rendering capabilities or simulation models that can be used in research projects depending on your needs. Since these tools are freely available, anyone can take advantage of them regardless of budget constraints; a definite plus. As an added bonus since they're open source programs they usually have large user communities that can answer questions you might have while using them–something commercial software may not always provide.
Overall, open source molecular science software provides a great way for scientists and researchers looking for powerful yet affordable tools without breaking their budgets.
What Software Does Open Source Molecular Science Software Integrate With?
Open source molecular science software can integrate with a wide variety of other types of software. These include programs for data visualization, analysis, computing, and modeling. Data visualization programs allow users to view their molecular models as three-dimensional images or animations. Analysis platforms help them to explore the data in order to visualize trends or correlations. Computing tools enable them to run complex calculations on their data sets quickly and efficiently. Lastly, modeling suites offer a range of features that let the user manipulate their structures in order to simulate potential outcomes of different experiments. All these types of software are integral components that open source molecular science projects rely on to create complete solutions for researchers and developers alike.
Trends Related to Open Source Molecular Science Software
- Increased Availability of Open Source Software: There has been an increase in the availability of open source molecular science software over the past few years. This is due to the growing popularity of open source software and its wide acceptance by researchers and scientists.
- Improved Quality of Open Source Software: With the increased availability of open source molecular science software, there has also been an improvement in the quality and features offered by these programs. Many of these programs have become more user-friendly, efficient, and reliable than their commercial counterparts.
- Growing Community: The open source movement has also created a vibrant community of developers and users who collaborate on new projects and help each other solve problems. This community is constantly working to improve existing software and develop new tools for molecular science.
- More Accessible Resources: Open source software has made it easier for researchers to access data and resources related to molecular science. These resources are usually free or easily accessible, so they can be used by anyone regardless of their budget or expertise.
- Cross-Platform Compatibility: Many open source molecular science software packages are now available for both Windows and Mac computers, making them more accessible to a wider range of users.
- Increased Efficiency: Open source software can reduce the time needed to complete complex tasks, such as analyzing large datasets or running simulations. This makes it easier for scientists to quickly analyze data and draw meaningful conclusions from it.
- Reduced Cost: The cost of using open source molecular science software is typically much lower than that of commercial programs. This makes it easier for researchers to access the tools they need without breaking the bank.
How Users Can Get Started With Open Source Molecular Science Software
Getting started with open source molecular science software can be a fairly straightforward process. The first step is to choose the specific software package that best fits your needs. There are many options out there, such as PyMol, Avogadro, VMD, APBS and more. You will need to do some research to determine which one offers the features and capabilities that are most important for your particular application.
Next, you will need to install the chosen software on your computer or server. This is normally done by downloading an installer from the main website of the project in question. You may also be able to find pre-built packages for some popular Linux distributions in their respective repositories (e.g., Ubuntu Software Center). If you are running MacOS or Windows, you may have additional steps required before installing; make sure to consult any relevant documentation beforehand.
Once installed, it's time to get familiar with how the interface works and all available features of the program. Whether through tutorials available online, documentation included in the download package or even trial-and-error experimentation. Be sure not to overlook any related programs or plugins too; they can sometimes provide highly useful functionality when combined with core packages like PyMol or Avogadro.
Finally, and this is especially true for more complex applications like molecular simulations, it is essential that you understand what data will be displayed by each graphical element before starting a simulation run. This way, you won't have any surprises later on when analyzing results. It would be a good idea at this point to look around for other users' experiences who have had success using similar tools as well as looking at example projects/tutorials provided by developers of said software alternatives. These could come in quite handy at some point.
To sum it up, getting started with open source molecular science software is not as difficult as it may seem initially. Researching the best choice for your specific application and following a few simple steps should put you on the right path towards making successful simulations or other types of analyses in no time.