{
    "abstract": "Advancements in the field of cancer research have enabled researchers and clinicians to access a massive amount of data to aid cancer patients and to add to the existing knowledge of research. However, despite the existence of reliable sources for extricating this data, it remains a challenge to accurately comprehend and draw conclusions based on the entirety of available information. Therefore, the current study aimed to design and develop a database for the identified variants of 5 different cancer types using 20 different cancer exomes. The exome data were retrieved from NCBI SRA and an NGS data clean-up protocol was implemented to obtain the best quality reads. The reads which passed the quality checks were then used for calling the variants which were then processed and filtered. This data was used to normalize and the normalized data generated was used for developing the database. MutaXome, which stands for mutations in cancer exome was designed in SQL, with the front end in bootstrap and HTML, and backend in PHP. The normalized data containing the variants inclusive of Single Nucleotide Polymorphisms (SNPs), were added into MutaXome, which contains detailed information regarding each type of identified variant. This database, available online via http://www.vidyalab.rf.gd/, serves as a knowledge base for cancer exome variations and holds much potential for enriching it by linking it to a decision support system as prospective studies.",
    "authors": [
        {
            "affiliation": "Department of Biotechnology, R V College of Engineering, Bengaluru, Karnataka, India.",
            "firstname": "P",
            "initials": "P",
            "lastname": "Padmavathi"
        },
        {
            "affiliation": "Department of Biotechnology, R V College of Engineering, Bengaluru, Karnataka, India.",
            "firstname": "K",
            "initials": "K",
            "lastname": "Chandrashekar"
        },
        {
            "affiliation": "Department of Biotechnology, R V College of Engineering, Bengaluru, Karnataka, India.",
            "firstname": "Anagha S",
            "initials": "AS",
            "lastname": "Setlur"
        },
        {
            "affiliation": "Department of Biotechnology, R V College of Engineering, Bengaluru, Karnataka, India.",
            "firstname": "Vidya",
            "initials": "V",
            "lastname": "Niranjan"
        }
    ],
    "conclusions": null,
    "copyrights": "\u00a9 The Author(s) 2022.",
    "doi": "10.1177/11769351221097593",
    "journal": "Cancer informatics",
    "keywords": [
        "Cancer exomes",
        "HTML and bootstrap",
        "PHP",
        "SQL",
        "database",
        "mutations"
    ],
    "methods": null,
    "publication_date": "2022-05-20",
    "pubmed_id": "35586731\n29038050\n22817889\n18772890\n24071849\n25417114\n25045606\n20393554\n24124232\n25369839\n12743998\n17525135\n20880996\n20525248\n30412573\n22318521\n22300766\n21062823\n28905005\n25538398\n22312429\n19451168\n22388286\n19505943\n20644199\n22435069\n32480002\n32958763\n34634815\n28781886\n33247936\n15188009\n26578591\n30380071",
    "results": null,
    "title": "MutaXome: A Novel Database for Identified Somatic Variations of ",
    "xml": "<Element 'PubmedArticle' at 0x788502f0c540>"
}