{
    "paper_id": "P01-1001",
    "header": {
        "generated_with": "S2ORC 1.0.0",
        "date_generated": "2023-01-19T09:30:16.833894Z"
    },
    "title": "Interpreting the human genome sequence, using stochastic grammars",
    "authors": [
        {
            "first": "Richard",
            "middle": [],
            "last": "Durbin",
            "suffix": "",
            "affiliation": {
                "laboratory": "",
                "institution": "The Sanger Centre Wellcome Trust Genome",
                "location": {
                    "addrLine": "Campus Hinxton",
                    "postCode": "CB10 1SA",
                    "settlement": "Cambridge",
                    "country": "UK"
                }
            },
            "email": "rd@sanger.ac.uk"
        }
    ],
    "year": "",
    "venue": null,
    "identifiers": {},
    "abstract": "The 3 billion base pair sequence of the human genome is now available, and attention is focusing on annotating it to extract biological meaning. I will discuss what we have obtained, and the methods that are being used to analyse biological sequences. In particular I will discuss approaches using stochastic grammars analogous to those used in computational linguistics, both for gene finding and protein family classification.",
    "pdf_parse": {
        "paper_id": "P01-1001",
        "_pdf_hash": "",
        "abstract": [
            {
                "text": "The 3 billion base pair sequence of the human genome is now available, and attention is focusing on annotating it to extract biological meaning. I will discuss what we have obtained, and the methods that are being used to analyse biological sequences. In particular I will discuss approaches using stochastic grammars analogous to those used in computational linguistics, both for gene finding and protein family classification.",
                "cite_spans": [],
                "ref_spans": [],
                "eq_spans": [],
                "section": "Abstract",
                "sec_num": null
            }
        ],
        "body_text": [],
        "back_matter": [],
        "bib_entries": {},
        "ref_entries": {}
    }
}