Provided are methods, system and software for diagnosis, prediction and prognosis of a cancer patient based on the quantitative level of a set of biomarkers. Also provided is a database for the purpose of recording the quantitative level of a set of biomarkers.

Provided are methods, system and software for diagnosis, prediction and prognosis of a cancer patient based on the quantitative level of a set of biomarkers. Also provided is a database for the purpose of recording the quantitative level of a set of biomarkers.

A screening system includes control circuitry that determines gene variants present in a compiled genome representative of a subject based on a difference between a reference genome and the compiled genome representative of the subject, and acquires phenotype information from an observation of the subject. The control circuitry further generates multi-dimensional data structure that includes the gene variants in respect of a first dimension, the phenotype information in respect of a second dimension; and a set of data samples in respect of a third dimension. The set of data samples includes the compiled genome sequence representative of the subject, and corresponding historical data samples of other subjects including their corresponding transcript information (for example, including phenotype information) of the other subjects and their gene variants. The control circuitry executes a gene variant interpretation using a correlation function to find phenotype-gene variant relationships based on the generated multi-dimensional data structure.

Methods of treatment based on a breast cancer's biomolecule response to targeted treatment are provided. Expression levels of various biomolecules or histological assessment of infiltrating immune cells after initiation of human epidermal growth factor receptor 2 (HER2) targeted treatment can be used to determine whether a breast cancer will achieve a pathologic complete response. Based on likelihood of a pathologic complete response, a breast cancer can be treated accordingly.

Methods of treatment based on a breast cancer's biomolecule response to targeted treatment are provided. Expression levels of various biomolecules or histological assessment of infiltrating immune cells after initiation of human epidermal growth factor receptor 2 (HER2) targeted treatment can be used to determine whether a breast cancer will achieve a pathologic complete response. Based on likelihood of a pathologic complete response, a breast cancer can be treated accordingly.

Provided are a method and system for screening neoantigen and uses of neoantigens. Specifically, provided are a method and system for screening neoantigens derived from a gene of which expression is essential for survival of a cancer cell and/or a is homogeneously expressed in all cells in cancer tissue as a diagnostic and/or therapeutic target, and uses of neoantigens.

Provided are a method and system for screening neoantigen and uses of neoantigens. Specifically, provided are a method and system for screening neoantigens derived from a gene of which expression is essential for survival of a cancer cell and/or a is homogeneously expressed in all cells in cancer tissue as a diagnostic and/or therapeutic target, and uses of neoantigens.

A platform providing methods and systems for prevention and/or treatment of a health condition, where a method can include: simultaneously reducing severity symptoms of the health condition and comorbid conditions upon: receiving a set of samples from one or more subjects; receiving a biometric dataset from one or more subjects; receiving a lifestyle dataset from one or more subjects; returning a genomic single nucleotide polymorphism (SNP) profile and a baseline microbiome state upon processing the set of samples, the biometric dataset, and the lifestyle dataset with a set of transformation operations; generating personalized intervention plans for the one or more subjects upon processing the genomic SNP profile and the baseline microbiome state with a multi-omic model; and executing the personalized intervention plans for the one or more subjects.

A platform providing methods and systems for prevention and/or treatment of a health condition, where a method can include: simultaneously reducing severity symptoms of the health condition and comorbid conditions upon: receiving a set of samples from one or more subjects; receiving a biometric dataset from one or more subjects; receiving a lifestyle dataset from one or more subjects; returning a genomic single nucleotide polymorphism (SNP) profile and a baseline microbiome state upon processing the set of samples, the biometric dataset, and the lifestyle dataset with a set of transformation operations; generating personalized intervention plans for the one or more subjects upon processing the genomic SNP profile and the baseline microbiome state with a multi-omic model; and executing the personalized intervention plans for the one or more subjects.

A method for application of a deep learning neural network (NN) for predicting the probability distribution of a biological phenotype does not require any assumption or prior knowledge of the probability distributions. The NN may be a recurrent neural network (RNN) or a long short-term memory (LSTM) network. The NN includes a loss function, which is trained on limited observations, as low as one observation, which is obtained from a large data set related to a biological system. The NN with the trained loss function is capable of calculating if readings that are outside of the mean for the data set are inherent to the biological system or are outlier readings. The output of the method is a continuous probability distribution of the biological phenotypes for each input parameter or set of parameters from the biological data set.