Abstract: Described are methods and systems for identifying phenotypic traits of an individual from nucleotide sequence data. The methods and systems are useful even when the identity of the individual or phenotypic traits of the individual is unknown.

Abstract: Systems, methods, and computer program products for machine translation are provided. In some implementations a system is provided. The system includes a language model including a collection of n-grams from a corpus, each n-gram having a corresponding relative frequency in the corpus and an order n corresponding to a number of tokens in the n-gram, each n-gram corresponding to a backoff n-gram having an order of n?1 and a collection of backoff scores, each backoff score associated with an n-gram, the backoff score determined as a function of a backoff factor and a relative frequency of a corresponding backoff n-gram in the corpus.

Abstract: Methods, systems, and apparatus, including computer program products, for correcting spelling in text. A text input is received for translation. One or more suspect words in the text input are identified. For each suspect word, one or more candidate words are identified. A score for the text input and scores for each of one or more candidate inputs are determined, where each candidate input is the text input with one or more of the suspect words each replaced by a respective candidate word. If any, a candidate input whose score is highest among the scores for the candidate inputs and is greater than the text input score by at least a threshold is selected. Otherwise, the text input is selected. A translation of a selected candidate input or the selected text input is provided as the translation of the text input.

Abstract: Methods, systems, and apparatus, including computer program products, for correcting spelling in text. A text input is received for translation. One or more suspect words in the text input are identified. For each suspect word, one or more candidate words are identified. A score for the text input and scores for each of one or more candidate inputs are determined, where each candidate input is the text input with one or more of the suspect words each replaced by a respective candidate word. If any, a candidate input whose score is highest among the scores for the candidate inputs and is greater than the text input score by at least a threshold is selected. Otherwise, the text input is selected. A translation of a selected candidate input or the selected text input is provided as the translation of the text input.

Abstract: Systems, methods, and computer program products for machine translation are provided. In some implementations a system is provided. The system includes a language model including a collection of n-grams from a corpus, each n-gram having a corresponding relative frequency in the corpus and an order n corresponding to a number of tokens in the n-gram, each n-gram corresponding to a backoff n-gram having an order of n-1 and a collection of backoff scores, each backoff score associated with an n-gram, the backoff score determined as a function of a backoff factor and a relative frequency of a corresponding backoff n-gram in the corpus.

Abstract: Systems, methods, and computer program products are provided for statistical machine translation. In some implementations a method is provided. The method includes receiving multi-lingual parallel text associating a source language, a target language, and one or more bridge languages, determining an alignment between the source language and the target language using a first bridge language that is distinct from the source language and the target language, and using the determined alignment to generate a candidate translation of an input text in the source language to the target language.

Abstract: Systems, methods, and computer program products for machine translation are provided. In some implementations a system is provided. The system includes a language model including a collection of n-grams from a corpus, each n-gram having a corresponding relative frequency in the corpus and an order n corresponding to a number of tokens in the n-gram, each n-gram corresponding to a backoff n-gram having an order of n-1 and a collection of backoff scores, each backoff score associated with an n-gram, the backoff score determined as a function of a backoff factor and a relative frequency of a corresponding backoff n-gram in the corpus.