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  • Can Ducks Eat Bird Seed? Everything You...

    Can Ducks Eat Bird Seed? There has been a growing understanding in…

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  • What Do Baby Birds Eat? Everything You...

    What Do Baby Birds Eat? For wild birds, spring is a hectic…

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  • Why Do Birds Migrate? Everything You Need...

    Why Do Birds Migrate? Traveling hundreds or even thousands of kilometres between…

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  • How Do Birds Communicate With Each Other?...

    How Do Birds Communicate With Each Other? Birds are among the most…

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  • How Do Birds Eat? Everything You Need...

    How Do Birds Eat? Birds don’t really chew or digest food in…

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  • Cryopreservation: Description, Techniques, & Protocols

    About Cryopreservation

    Serial sub-culturing is a time consuming and can lead to contamination or genetic drift as smaller and smaller portions of a population are selected.

    However, a cell populations can be stabilized by subjecting them to cryogenic temperatures. Stabilizition of cells at cryogenic temperatures is called cryopreservation.

    What is Cryopreservation?

    Ice forms at different rates during the cooling process.

    As ice forms, water is removed from the extracellular environment and an osmotic imbalance occurs across the cell membrane leading to loss of water from the cell.

    The increase in solute concentration can be detrimental to cell survival.

    Too much water retention inside the cell cause damage to the cells and thus reduce the cell viability due to ice crystal formation and recrystallization during warming can occur.

    The rate of cooling has a dramatic effect on over all cryopreservation process.

    Rapid cooling minimizes the solute concentration and thus affects the uniform ice formion, but leads to more intracellular ice.

    On the other hand, slow cooling, results in a greater loss of water from the cell and less internal ice, but increases the solution effects.

    A cooling rate of 1°C per minute is generally preferred. Cryoprotective additives or chemicals, for example dimethylsulfoxide (DMSO) and glycerol can protect the cells during freezing and minimize the detrimental effects of increased solute concentration and ice crystal formation.

    Cryopreservation media generally consists of a base medium, cryopreservative and a protein source.

    The cryopreservative and protein protect the cells from the stress of the freeze-thaw process.

    Additionally, it maintains frozen cells at the proper storage temperature and using an appropriate warming rate will minimize damage to frozen cells.

    Cryopreservation - Research Tweet 1

    Adopted from BioRender

    Cryopreservation Requirements

    Sterile:

    1. Culture to be frozen

    2. If monolayer: PBS and 0.25% trypsin (for adherent cells)

    3. Growth medium with serum (If serum is being used with serum-free cultures, it should be washed off after thawing)

    4. Cryoprotectant DMSO or glycerol, (free of impurities)

    5. Pipette

    6. Cryovials (1.0 ml), prelabeled with the cell line designation and the date of freezing

    Non sterile:

    7. Hemocytometer

    8. Insulated container for freezing (Ice box)

    9. Protective gloves, nitrile

    Cryopreservation Procedure

    1. Before cryopreservation, cells should be characterized and checked for contamination.

    2. Check visually and on microscope for healthy appearance, morphological characteristics.

    3. Grow the culture up to the late log phase and if cells are as a monolayer, trypsinize and count the cells.

    If suspension is used count, centrifuge the cells and resuspend at 2 × 10^6–2 × 10^7 cells/ml.

    4. Constitute the freezing media by adding 90% serum and 10% v/v DMSO.

    5. Dilute the cell suspension in ratio of 1:1 with freezing medium to give approximately 1 × 10^6 –1 × 10^7 cells/ml

    6. Dispense the cell suspensions into pre-labeled cryovials.

    7. Allow slow freezing by keeping vials at 4 °C followed by -20 °C and finally stored at – 80 °C (storage in liquid nitrogen is preferable).

    8. When the vials are safely located in the freezer, complete the appropriate entries in the freezer index.

    Cryopreservation Precaution

    Cells harvested for cryopreservation should be at their optimum viability to ensure maximum survival during freezing and after thawing.

    This is especially relevant when the method of cryopreservation reduces the number of viable cells and increases the chances of selecting freeze-tolerant populations that may have different characteristics from the original population.

    DMSO is toxic if left in contact with cells for more than a short period of time. Once the cells have been prepared for freezing, they should be ampuled and frozen as soon as possible.

    DMSO can penetrate many synthetic and natural membranes, including skin.

    Hence, DMSO should always be handled with caution, particularly in the presence of any toxic substances.

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  • Animal Cells: Labelled Diagram, Definitions, and Structure

    What is a Cell?

    In biology, cell is the smallest unit that can live on its own and that makes up all living organisms and the tissues of the body. A cell has three main parts: the cell membrane, the nucleus, and the cytoplasm.

    What is Animal Cell?

    Animals are made of eukaryotic cells having nucleus, cellular organelles, and are surrounded by a cell membrane or plasma membrane.

    What is Plant Cell?

    Plant cell are the basic unit of all plants. Plant cells, like animal cells, are eukaryotic, meaning they have a membrane-bound nucleus and organelles.

    Animal Cells Diagram

    Plant Cell vs Animal Cell, Plant Cell labelled, Plant Cell Diagram,

    Animal Cells Organelles and Functions

    Cell Organelles Functions
    Cell MembraneA double layer that supports and protects the cell. Allows materials in and out.
    NucleusThe control center of the cell. Nucleus  contains majority of cell’s the DNA
    MitochondriaPopularly known as the “Powerhouse”. Breaks down food to produce energy in the form of ATP.
    Golgi BodyProcesses and packages materials for the cell.
    LysosomeContains digestive enzymes that destroy damaged organelles and invaders.
    Rough E.R.Builds and transports substances through the cell. Has ribosomes on it.
    Smooth E.R.Builds and transports substances through the cell. Does not have ribosomes.
    CytoplasmJelly-like fluid that surrounds and protects the organelles.
    RibosomeHelps make protein for the cell.
    VacuoleStores food and water.
    NucleolusA round structure in the nucleus that makes ribosomes.
    Nuclear MembraneSurrounds the nucleus.

    Plant Cells Diagram

    Labelled Plant Cells

    Plant Cells Organelles and Functions

    Cell Organelles Functions
    Cell WallGives shape and protection to plant cells.
    Chloroplast
    Changes sunlight into sugar for plant cells. Contains a green pigment called chlorophyll.
    Cell MembraneA double layer that supports and protects the cell. Allows materials in and out.
    NucleusThe control center of the cell. Nucleus  contains majority of cell’s the DNA
    MitochondriaPopularly known as the “Powerhouse”. Breaks down food to produce energy in the form of ATP.
    Golgi BodyProcesses and packages materials for the cell.
    LysosomeContains digestive enzymes that destroy damaged organelles and invaders.
    Rough E.R.Builds and transports substances through the cell. Has ribosomes on it.
    Smooth E.R.Builds and transports substances through the cell. Does not have ribosomes.
    CytoplasmJelly-like fluid that surrounds and protects the organelles.
    RibosomeHelps make protein for the cell.
    VacuoleStores food and water.
    NucleolusA round structure in the nucleus that makes ribosomes.
    Nuclear MembraneSurrounds the nucleus.

    Animals Cells Vs Plant Cells

    Plant and animal cells have several differences such as plant cells have a cell wall or chloroplasts, but animal cells do not have either. Plant cells are fixed, rectangular in shapes, but animal cells are mostly round and irregular in shape.

    On the other hand, plant and animal cells are both eukaryotic cells, so they have several features in common, such as the presence of a cell membrane, and cell organelles, like the nucleus, mitochondria and endoplasmic reticulum.

    Cell Organelles Plant CellsAnimal Cells
    Cell wallPresent (made up of cellulose)Absent
    ShapeRectangular (fixed shape)Round (irregular shape)
    VacuoleOne, large central vacuole taking up to 90% of cell volume.One or more small vacuoles (much smaller than plant cells).
    CentriolesOnly present in lower plant forms (e.g. chlamydomonas)Present in all animal cells
    ChloroplastPlant cells have chloroplasts to synthesize their own food.Absent
    Plasma MembraneCell wall and a cell membraneOnly cell membrane
    FlagellaPresent in some cells (e.g. sperm of bryophytes and pteridophytes, cycads and Ginkgo)Present in some cells ( e.g. mammalian sperm cells)
    CiliaMost plant cells do not contain cilia.Present
    LysosomesLysosomes usually not evident.Lysosomes occur in cytoplasm.
    CytoplasmPresentPresent
    RibosomesPresentPresent
    MitochondriaPresentPresent
    Plastids PresentAbsent
    Endoplasmic ReticulumPresentPresent
    PeroxisomesPresent
    Golgi ApparatusPresentPresent
    Microtubules/ MicrofilamentsPresentPresent
    NucleusPresentPresent
    Cilia and Flagella

    Some eukaryotic cells either have cilia or flagella. Cilia are small, wiggling arm-like structures, whereas flagella are like a tail.

    Both structures are made of long protein fibers called microtubules, with a structure where nine microtubules form a ring around two central microtubules.

    Cell Membrane
    Cell Membrane, Cell Membrane Function, Cell Membrane Structure, What is Cell Membrane,

    The cell membrane encloses the cell’s contents. It monitors what comes in, and what goes out. It has a characteristic called semi permeability, meaning it can “choose” what molecules can come in and out of the cell.

    Cytoplasm / Cytoskeleton / Centrosomes

    There are water and nutrients within the cell. The cytoskeleton is a collection of protein strands that reinforce the cell.

    Centrosomes are a part of this reinforcement. They assemble long microtubules out of proteins. The cytoplasm provides the infrastructure that is necessary for cells to thrive and for the organelles to do their jobs within the cell.

    The nucleus of the cell has its own type of cytoplasm, called the nucleoplasm.

    Endoplasmic Reticulum
    Endoplasmic Reticulum, Endoplasmic Reticulum Definition, Endoplasmic Reticulum Function, Endoplasmic Reticulum Structure 4

    The endoplasmic reticulum(s) are organelles that create a network of membranes that transport substances around the cell.

    They have phospholipid bilayers. There are two types of ER: the rough ER, and the smooth ER. The rough endoplasmic reticulum is rough because it has ribosomes (which is explained below) attached to it. It helps in the synthesis and packaging of proteins.

    The smooth endoplasmic reticulum doesn’t have ribosomes attached. It contains enzymes that help with the creation of important lipids. It has a role in the process of cell detoxification or removal of waste materials. The smooth ER adds a carboxyl group to noxious substances, making them soluble in water.

    Ribosomes
    Ribosomes- Function, Definition, Structure, and Formation - research tweet 1

    Ribosomes create proteins. They can float freely in the cytoplasm or can be attached to the nuclear envelope. They create proteins by assembling amino acids into polypeptides.

    As the ribosomes build an amino acid chain, the chain is pushed into the endoplasmic reticulum. When the protein chain is complete, the endoplasmic reticulum pinches it off and sends it to the Golgi apparatus.

    Golgi Apparatus
    Golgi Apparatus, Golgi Apparatus Function, Golgi Apparatus Definition, 1

    The Golgi apparatus focuses on protein processing and packaging. Golgi bodies are the Golgi apparatus’s layers. Golgi bodies cut up large proteins into smaller hormones.

    They can combine proteins with carbohydrates to make various molecules. They then package these products into sacs like structure popularly known as called vesicles, which  ship the products of the Golgi body to other parts of the cell, and outside the cell as well.

    Lysosomes
    Lysosome - Research Tweet 3

    Lysosomes are enzyme sacs that break down cellular waste – they process cell digestion. They can take substances from outside of the cell and cellular waste and turn them into simple compounds.

    The compounds are then transferred into the cytoplasm where they can be used as a cell building material.

    Nucleus
    Structure of Nucleus - Research Tweet 1

    The nucleus is a highly specialized organelle that lives in its own double membrane with the nucleolus. The nucleus stores the cell’s DNA and holds all the information the cell needs to do its job.

    Chromatin is a web-like substance that holds the nucleus’s DNA. Chromatin gathers into rod-shaped chromosomes that hold DNA molecules when the cell is ready to split during cell division.

    The nucleolus lives inside the nucleus and is the only organelle that is not enveloped by its own membrane. It makes ribosomal RNA, rRNA, which is important during protein synthesis.

    Gene Nucleotides: Definition, Functions, Types, and Examples

    Ribosomal RNA or rRNA combines with proteins to form the basic units of ribosomes. When the units are done, the nucleus spits them out of the nuclear envelope, where they are assembled into ribosomes.

    The nucleus sends orders in the form of messenger RNA, or mRNA. The messages are sent to ribosomes, which carry out the orders in the rest of the cell.

    Mitochondria
    Mitochondria, What is Chemiosmosis, Chemiosmosis definition, Chemiosmosis in Photosynthesis, Chemiosmosis process,

    The mitochondria is the “power house” of the cell. This is where cellular respiration takes place. During this, energy is derived and converted into ATP from fats, carbohydrates, and other biomolecules.

    Mitochondria almost act as independent cellular organelle and have their own DNA, know as mitochondrial DNA (mtDNA) which is an exact replication of the mother’s DNA.

    Animal Cells Citations

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  • 15 Most Popular Machine Learning Software Tools...

    15 Most Popular Machine Learning Software Tools In 2022

    With the help of machine learning systems, we can examine data, learn from that data and make decisions. Machine learning involves algorithms and Machine learning library is a bundle of algorithms.

    List of 15 Most Popular Machine Learning Software Tools In 2022

    (1) Scikit-learn

    Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. It also provides various tools for model fitting, data preprocessing, model selection, model evaluation, and many other utilities.

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    (2) PyTorch

    With TorchScript, PyTorch provides ease-of-use and flexibility in eager mode, while seamlessly transitioning to graph mode for speed, optimization, and functionality in C++ runtime environments.

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    (3) TensorFlow

    TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications.

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    (4) Weka 3: Machine Learning Software in Java

    Weka is a collection of machine learning algorithms for data mining tasks. It contains tools for data preparation, classification, regression, clustering, association rules mining, and visualization. Found only on the islands of New Zealand, the Weka is a flightless bird with an inquisitive nature.

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    (5) KNIME

    At KNIME, we build software to create and productionize data science using one easy and intuitive environment, enabling every stakeholder in the data science process to focus on what they do best. 

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    (6) Colab

    Summary of PhD Program: Whether you’re a student, a data scientist or an AI researcher, Colab can make your work easier. The document you are reading is not a static web page, but an interactive environment called a Colab notebook that lets you write and execute code.

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    (7) Apache Mahout

    Apache Mahout is a project of the Apache Software Foundation to produce free implementations of distributed or otherwise scalable machine learning algorithms focused primarily on linear algebra. 

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    (8) Accord.Net

    The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and an extensive documentation and wiki helps fill in the details.

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    (9) Shogun Machine Learning

    Shogun is a free, open-source machine learning software library written in C++. It offers numerous algorithms and data structures for machine learning problems. 

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    (10) Keras.io

    Keras is an API designed for human beings, not machines. Keras follows best practices for reducing cognitive load: it offers consistent & simple APIs, it minimizes the number of user actions required for common use cases, and it provides clear & actionable error messages. It also has extensive documentation and developer guides. 

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    (11) Rapid Miner

    RapidMiner’s data science platform delivers transformational business impact for over 40,000+ organizations in every industry to drive revenue, reduce costs, and avoid risks. 

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    (12) Amazon Machine Learning (AML)

    Make accurate predictions, get deeper insights from your data, reduce operational overhead, and improve customer experience with AWS machine learning (ML). AWS helps you at every stage of your ML adoption journey with the most comprehensive set of artificial intelligence (AI) and ML services, infrastructure, and implementation resources.

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    (13) Oryx 2

    Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large scale machine learning. It is a framework for building applications, but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. 

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    (14) Apache Spark MLlib

    MLlib fits into Spark’s APIs and interoperates with NumPy in Python (as of Spark 0.9) and R libraries (as of Spark 1.5). You can use any Hadoop data source (e.g. HDFS, HBase, or local files), making it easy to plug into Hadoop workflows.

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    (15) Core ML Machine Learning Algorithm

    Core ML applies a machine learning algorithm to a set of training data to create a model. You use a model to make predictions based on new input data. Models can accomplish a wide variety of tasks that would be difficult or impractical to write in code. For example, you can train a model to categorize photos, or detect specific objects within a photo directly from its pixels.

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  • 15 Best Free Bioinformatics Tools for Genomic...

    15 Best Free Bioinformatics Tools for Genomic Testing 2022

    Popular applications for bioinformatics are best for sequence analysis and curations. The best solutions in the field have key inbuilt computational and big data analysis tools for genome sequencing. Let us have a look at what else these applications are comprised of in the following list.

    List of 15 Best Free Bioinformatics Tools for Genomic Testing 2022

    (1) geWorkbench

    Summary of PhD Program: geWorkbench is an open-source bioinformatics platform that offers a comprehensive and extensible collection of tools for the management, analysis, visualization, and annotation of biomedical data. Many kinds of analysis are supported. For microarrays, there are tools for filtering and normalization, basic statistical analyses, clustering, network reverse engineering, as well as many common visualization tools.

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    (2) BioPerl

    BioPerl is a collection of Perl modules that facilitate the development of Perl scripts for bioinformatics applications. It has played an integral role in the Human Genome Project.

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    (3) Unipro UGENE - Integrated Bioinformatics Tools

    UGENE is free open-source cross-platform bioinformatics software It works perfectly on Windows, macOS and Linux and requires only a few clicks to install.

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    (4) BioJava

    BioJava will run on any computer with a Java virtual machine complying to the Java specifications. Java implementations for Linux, Windows, and Solaris are available to download from Oracle’s java website. Recent versions of MacOS X include a suitable Java implementation as standard. Java is also available on many other platforms: if in doubt, contact your vendor. BioJava binaries are distributed in .jar (Java ARchive) format.

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    (5) Biopython

    Biopython is a set of freely available tools for biological computation written in Python by an international team of developers. It is a distributed collaborative effort to develop Python libraries and applications which address the needs of current and future work in bioinformatics. The source code is made available under the Biopython License, which is extremely liberal and compatible with almost every license in the world.

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    (6) InterMine

    InterMine integrates heterogenous data sources, making it easy to query and analyse data. InterMine’s tables allow you to easily drill down into data. It’s easy to filter data, add additional columns, navigate to report pages.

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    (7) Integrative Genomics Viewer (IGV)

    The Integrative Genomics Viewer (IGV) is a high-performance, easy-to-use, interactive tool for the visual exploration of genomic data. It supports flexible integration of all the common types of genomic data and metadata, investigator-generated or publicly available, loaded from local or cloud sources. 

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    (8) GROMACS

    GROMACS is a versatile package to perform molecular dynamics, i.e. simulate the Newtonian equations of motion for systems with hundreds to millions of particles. It is primarily designed for biochemical molecules like proteins, lipids and nucleic acids that have a lot of complicated bonded interactions, but since GROMACS is extremely fast at calculating the nonbonded interactions (that usually dominate simulations) many groups are also using it for research on non-biological systems, e.g. polymers.

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    (9) Taverna Workbench Bioinformatics 2.5

    Taverna Workbench Bioinformatics is an edition of Taverna Workbench that includes support for building and executing bioinformatics workflows using bioinformatics data and analytical services such as BioMart and BioMoby.

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    (10) EMBOSS

    EMBOSS is “The European Molecular Biology Open Software Suite”. EMBOSS is a free Open Source software analysis package specially developed for the needs of the molecular biology (e.g. EMBnet) user community. The software automatically copes with data in a variety of formats and even allows transparent retrieval of sequence data from the web. Also, as extensive libraries are provided with the package, it is a platform to allow other scientists to develop and release software in true open source spirit. EMBOSS also integrates a range of currently available packages and tools for sequence analysis into a seamless whole. EMBOSS breaks the historical trend towards commercial software packages.

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    (11) Clustal Omega

    Clustal Omega is the latest addition to the Clustal family. It offers a significant increase in scalability over previous versions, allowing hundreds of thousands of sequences to be aligned in only a few hours. It will also make use of multiple processors, where present. In addition, the quality of alignments is superior to previous versions, as measured by a range of popular benchmarks.

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    (12) BLAST

    The Basic Local Alignment Search Tool (BLAST) finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches. BLAST can be used to infer functional and evolutionary relationships between sequences as well as help identify members of gene families. 

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    (13) bedtools

    Collectively, the bedtools utilities are a swiss-army knife of tools for a wide-range of genomics analysis tasks. The most widely-used tools enable genome arithmetic: that is, set theory on the genome. For example, bedtools allows one to intersect, merge, count, complement, and shuffle genomic intervals from multiple files in widely-used genomic file formats such as BAM, BED, GFF/GTF, VCF. While each individual tool is designed to do a relatively simple task (e.g., intersect two interval files), quite sophisticated analyses can be conducted by combining multiple bedtools operations on the UNIX command line. 

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    (14) Bioclipse Open Source Bioinformatics Tool

    Bioclipse is a rich client, which means it is a downloadable application that run on your local computer but also gives the possibility to communicate with servers for data retrieval and computational services. The powerful plugin architecture is based on Eclipse, and results in a responsive, integrated user interface designed for simple and intuitive operations that at the same time is easy to extend with custom functionality.

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    (15) Bioconductor

    The mission of the Bioconductor project is to develop, support, and disseminate free open source software that facilitates rigorous and reproducible analysis of data from current and emerging biological assays. We are dedicated to building a diverse, collaborative, and welcoming community of developers and data scientists. 

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  • Top 15 Best Statistical Software Free in...

    Top 15 Best Statistical Software Free in 2022 (Statistics and Data Analysis)

    What Are Statistical Software?

    Statistical software, or statistical analysis software, refers to tools that assist in the statistics-based collection and analysis of data to provide science-based insights into patterns and trends. They often use statistical analysis theorems and methodologies, such as regression analysis and time series analysis to perform data science.

    List of Top 15 Best Statistical Software Free in 2022 (Statistics and Data Analysis)

    (1) SAS® software

    Whether you’re a professor, teacher, student or independent learner, you can get easy access to powerful SAS software via the cloud. Setup is easy, too. After you get set up, a broadband internet connection is all you’ll need to run the best analytics software in the world.

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    (2) GNU PSPP

    PSPP is a stable and reliable application. It can perform descriptive statistics, T-tests, anova, linear and logistic regression, measures of association, cluster analysis, reliability and factor analysis, non-parametric tests and more. Its backend is designed to perform its analyses as fast as possible, regardless of the size of the input data. You can use PSPP with its graphical interface or the more traditional syntax commands.

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    (3) Statistical Lab

    The Statistical Lab is an explorative and interactive tool designed both to support education in statistics and provide a tool for the simulation and solution of statistical problems. The graphical user interface is designed to make complex statistical relations easy to understand. It connects and displays data frames, frequency tables, random numbers or matrixes in a user-friendly statistical worksheet allowing users to run calculations, conduct analyses and perform multiple simulations and manipulations.

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    (4) Develve Statistical Analysis Software

    Statistical software for fast and easy interpretation of experimental data in science and R&D in a technical environment. This statistical package helps with analysis and prevents making false assumptions. In short it makes statistics faster and easier, suitable for less experience users but advanced enough for more demanding users.

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    (5) IBM SPSS Statistical Analysis Software

    IBM® SPSS® Statistics is a powerful statistical software platform. It offers a user-friendly interface and a robust set of features that lets your organization quickly extract actionable insights from your data. Advanced statistical procedures help ensure high accuracy and quality decision making. All facets of the analytics lifecycle are included, from data preparation and management to analysis and reporting.

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    (6) Stata: Statistical software for data science

    Fast. Accurate. Easy to use. Stata is a complete, integrated software package that provides all your data science needs—data manipulation, visualization, statistics, and automated reporting.

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    (7) Minitab: Data Analysis, Statistical & Process Improvement Tools

    Data is everywhere, but are you truly taking advantage of yours? Minitab Statistical Software can look at current and past data to discover trends, find and predict patterns, uncover hidden relationships between variables, and create stunning visualizations to tackle even the most daunting challenges and opportunities. With powerful statistics, industry-leading data analytics, and dynamic visualizations on your side, the possibilities are endless.

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    (8) GraphPad Prism

    A versatile statistics tool purpose-built for scientists-not statisticians. Get a head start by entering data into tables that are structured for scientific research and guide you to statistical analyses that streamline your research workflow. No coding required.

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    (9) DataMelt

    DataMelt is a free software for numeric computation, mathematics, statistics, symbolic calculations, data analysis and data visualization. This multiplatform program combines the simplicity of scripting languages, such as Python, Ruby, Groovy (and others), with the power of hundreds of Java packages.

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    (10) GNU Octave

    Powerful mathematics-oriented syntax with built-in 2D/3D plotting and visualization tools. Free software, runs on GNU/Linux, macOS, BSD, and Microsoft Windows. Drop-in compatible with many Matlab scripts

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    (11) SOFA Statistics

    SOFA is a user-friendly statistics, analysis, & reporting program. It is free, with an emphasis on ease of use, learn as you go, and beautiful output. SOFA lets you display results in an attractive format ready to share. And SOFA will help you learn as you go.

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    (12) Dataplot

    Dataplot® is a free, public-domain, multi-platform (Unix/Linux, MacOS, Windows 7/8/10) software system for scientific visualization, statistical analysis, and non-linear modeling. The target Dataplot user is the researcher and analyst engaged in the characterization, modeling, visualization, analysis, monitoring, and optimization of scientific and engineering processes.

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    (13) SCIPY

    SciPy is a set of open source (BSD licensed) scientific and numerical tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient optimization, parallel programming tools, an expression-to-C++ compiler for fast execution, and others. A good rule of thumb is that if it’s covered in a general textbook on numerical computing (for example, the well-known Numerical Recipes series), it’s probably implemented in SciPy.

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    (14) Zelig

    Zelig is an easy-to-use, free, open source, general purpose statistics program for estimating, interpreting, and presenting results from any statistical method. Zelig turns the power of R, with thousands of open source packages — but with free ranging syntax, diverse examples, and documentation written for different audiences — into the same three commands and consistent documentation for every method.

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    (15) MacAnova

    MacAnova is a free, open source, interactive statistical analysis program for Windows, Macintosh, and Linux written by Gary W. Oehlert and Christopher Bingham, both of the School of Statistics, University of Minnesota. In spite of its name, MacAnova is not just for Macintosh computers and not just for doing Analysis of Variance.

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