Please enable JavaScript.

Coggle requires JavaScript to display documents.

G4-Big Data Analytics in Bioinformatics, There are primarily five types of…

- - - - Great for highly structured data and working with complex queries and reports
      - A mix of open-source like Postgres & MySQL, and commercial like Oracle Database.
      - Oracle, Postgres, and MS-SQL.
      - -Table-Based with fixed rows and columns
        -General Purpose
      - Relational Database
    - - MongoDB, Redis, Neo4j, Cassandra, Hbase.
      - Open Source
      - document based, key-value pairs, graph databases, column-oriented DB
        
        -Document: general purpose
        -Key-value: large amounts of data with simple lookup queries
        -Wide-column: large amounts of data with predictable query patterns
        -Graph: analyzing and traversing relationships between connected data
      - Pair well with fast paced, agile development teams and expecting high transaction load.
      - Non-relational database or distributed database
  - - - Can be difficult to scale
      - Time consuming to understand and design the structure of the database
    - - Unsuited for interconnected data
      - Can have slower response time
      - Technology still maturing
- - - - No formal process
      - No algorithms
      - No rules
  - - - also known as Denormalized models
      - Example
        
        Codes
        
        {
        _id: <ObjectId1>,
        username: “123xyz”,
        contact: {
        phone: “123-456-7890”,
        email: “xyz@example.com”
        },
        access: {
        level: 5,
        group: “dev”
        }
        }
        
        Explaination from the above codes
        
        the first { ... } stand for the main data
        
        the second and third {...} in the first {...} are the embedded sub-document
        
        this shows that this models allow applications to store related information in the same database record.
      - used when
        
        have "contains" relationship between entities (One-to-One)
        
        have one-to-many relationships between entities where the child documents always appear with or are viewed in the context of the parent documents
    - - also called Referencing scheme model
      - it's referencing another document using a document's unique object ID and connecting them together using the $lookup operator
      - Example
        
        USER DOCUMENT
        {
        _id: <ObjectId1>,
        username: "123xyz"
        }
        
        CONTACT DOCUMENT
        {
        _id: <ObjectId2>,
        user_id: <ObjectId1>,
        phone: "123-456-7890",
        email: "xyz@example.com"
        }
        
        ACCESS DOCUMENT
        {
        _id: <ObjectId3>,
        user_id: <ObjectId1>,
        level: 5,
        group: "dev"
        }
        
        Explanation for the codes above
        
        The data are stored in different documents
        
        _id from the USER DOCUMENT are use to be the unique ID (user_id) to call the contact and access information in their respective documents
        
        to operate this function it will use $lookup operator (from MongoDB3.2) or $graphLookup operator (from MongoDB3.4)
      - used when
        
        embedding would result in duplication of data
        
        to represent more complex many-to-many relationships
        
        to model large hierarchical data sets
- - - - Nephele - perform genotyping via complete composition vector algorithm.
      - Cloudgene -a graphical user interface to support processing and analysis of large scale of data.
      - CloudAligner- map short read sequence
      - Genome Analysis Toolkit (another software developed using MapReduce platform for robust analysis of next generation DNA sequencing data.
    - - Contrail - generates a de novo assembly of short sequence reads scaled up by de Brujin graph.
      - Myrna- computing the short read alignment for RNA.
      - Crossbow platform - whole genome resequencing for short reads along with SNP genotyping analysis
        (Langmead, B et al., 2009,
        https://github.com/BenLangmead/crossbow)
  - - - Extremely large big data sets that may be analysed computationally to reveal patterns, trends, and it is heterogeneous and not specific to a particular field
      - high-volume, high velocity/ high-variety information assets that demand cost-effective innovative forms of information processing that enable enhanced insight, decision making, and process automation
    - - Biology
        
        Two (2) main brisk vicissitudes:
        
        Capabilities of the computers and software tools
        
        progression in molecular biology experiments producing enormous amount of data
        
        No longer limited to particular field or search-engine/ indexes
        
        Automated genome sequences, DNA computing and many more giving rise to this new era of big data in bioinformatics
        
        mould massive mounts of information into a better understanding of the basic biological mechanism and how the results can be applied in.
      - Gene Sequence
        
        The Human Genome Project (HGP) in the early 2000s
        
        Identifying how human genetics work has required more serious study with more supplies
      - Preventative medicine
        
        To solve complex biological problem
        
        To provide better foundation to produce and develop preventative, predictive in the field of medical science
        
        Improve the health of patients and give a better diagnose while treating the deases
      - Healthcare
        
        By keeping its record and maintain its requirement in patient's heath and care
        
        Easy to identify and fraud claims, it helps in transformation of medical claims payment system
        
        Easy to treat a wide range of conditions
      - Industry
        
        Support the scientific study of complex biological problems
        
        This visualisation creates the more need for information along with the data mining, digital libraries, modelling and simulation and other information
      - Personalized Medicine
        
        Studying various ways to collaborate and coordinate medicine with new technologies
        
        Developed to reduced cost to improve patient's safety and healthcare quality
        
        Offers the chance of better health with less harm