An Accelerated Progression Relapse Test (APRT) and method is provided for use in the prognosis of a patient having an ER+ breast cancer. The APRT provides a determination of when a patient in a particular diseased state is likely to benefit from further disease treatment, or does not have a high probability of benefit with additional treatment. Four genetic probes are disclosed that target the MKI67, CDC6 and SPAG5 gene and gene products. The ER+ breast cancer patient population is stratified into two groups, with the low gene expression group identifying the patient/patient group that is less likely to benefit from additional treatment measures, and a high gene expression group identifying the patient group that is more likely to benefit from additional treatment measures.

A microarray analysis method, in which a microarray obtained by arranging probes on a substrate surface having an irregular shape is irradiated with excitation light and fluorescence amounts of the probes excited by the excitation light are obtained as numerical data, includes a step (a) of measuring the fluorescence amounts of the probes to acquire fluorescence image data, a step (b) of receiving reflected light and/or scattered light from the substrate surface to acquire the irregular shape of the substrate surface of the microarray as alignment image data based on the light receiving intensities of the light, and a step (c) of determining positions of the probes on the fluorescence image data based on the alignment image data.

An apparatus comprising: a value receiver, configured to receive fluorescence values measured during a chemical reaction involving a test sample, each value pertaining to a respective physical parameter value, a difference calculator, configured to calculate differences, each difference being between respective one of the measured fluorescence values and one of reference fluorescence values of a reference sample, each reference fluorescence value pertaining to a respective physical parameter value, a cumulative index calculator, configured to calculate a cumulative index, by selecting a first difference among the calculated differences, and selecting and adding to the first difference differences, each one of the added differences being selected according to a proximity standard applied on each two differences selected in a sequence, the proximity standard being based on proximity of physical parameter values and difference size, and a similarity determiner, configured to determine similarity between the samples, using the calculated cumulative index.

A method for estimating the affinity φ of a first DNA strand, or “probe”, to be hybridized with a second DNA strand, or “target”, to form a hybrid of length L.sub.bp, the method comprising: in each division of a set of M divisions of the hybrid, counting the number of times in which each hybrid of a set of P DNA strand hybrids is present in the division, the hybrids being of length k less than the length L.sub.bp, or “k-hybrids”; for each combination of mismatches of a set of L combinations of mismatches in a hybrid of length Lbp, determining whether the pair of mismatches is present in the hybrid; and calculating the affinity φ according to the relation:

[00001]$\phi =\underset{m=1}{\overset{M}{.Math.}}.Math.\underset{p=1}{\overset{P}{.Math.}}.Math.x_{m,p}.Math.{\hat{\beta }}_{m,p}+\alpha$

A novel method to predict toxicity and dose-dependent effects of an agent based on transcriptomic data analysis, by determining a predictive toxicogenomics space (PTGS) score. The PTGS score helps to predict and model the toxicity of compounds typically consisting of chemicals, pharmaceuticals, cosmetics and agrochemicals. The invention further comprises methods of deriving the PTGS score, as well as computer programs to calculate PTGS scores.

The present description relates to peptides, proteins, nucleic acids and cells for use in immunotherapeutic methods. In particular, the present description relates to the immunotherapy of cancer. The present description further relates to tumor-associated T-cell peptide epitopes, alone or in combination with other tumor-associated peptides that can for example serve as active pharmaceutical ingredients of vaccine compositions that stimulate anti-tumor immune responses, or to stimulate T-cells ex vivo and transfer into patients. Peptides bound to molecules of the major histocompatibility complex (MHC), or peptides as such, can also be targets of antibodies, soluble T-cell receptors, and other binding molecules.

Developmental, stem cell and cancer biologists are interested in the molecular definition of cellular differentiation. Although single-cell RNA sequencing represents a transformational advance for global gene analyses, novel obstacles have emerged, including the computational management of dropout events, the reconstruction of biological pathways and the isolation of target cell populations. Provided herein is an algorithm named dpath that applies the concept of metagene entropy and allows the ranking of cells based on their differentiation potential. Also provided herein are self-organizing map (SOM) and random walk with restart (RWR) algorithms to separate the progenitors from the differentiated cells and reconstruct the lineage hierarchies in an unbiased manner. These algorithms were tested using single cells from Etv2-EYFP transgenic mouse embryos and reveal specific molecular pathways that direct differentiation programs involving the haemato-endothelial lineages. This software program quantitatively assesses the progenitor and committed states in single-cell RNA-seq data sets in a non-biased manner.

The inventive subject matter relates broadly to novel techniques for identification and comparative analysis of sequence features in metagenomic whole-genome shotgun (WGS) sequence data associated with particular disease states in a subject. More particularly, the inventive subject matter relates to diagnostic methods for distinguishing between different types of inflammatory bowel disease in a subject based on the microbial community signature of the subject.

Devices, systems, and methods for automatic genotyping obtain high-resolution melt data from a test sample defining a melting curve for a target nucleic acid in the test sample; obtain high-resolution melt data from a control sample defining a melting curve for a wild type of the target nucleic acid in the control sample; calculate melting curve derivatives of the melting curves for the test sample and the control sample, respectively, wherein each melting curve derivative represents a negative derivative of a fluorescence emitted from a nucleic acid sample as a function of temperature affecting nucleic acid denaturation; calculate parameters defining differences between features of the test sample and the control sample melting curve derivatives; and assign a genotype to the test sample based on a comparison of the calculated parameters to predetermined thresholds and boundaries defining genotypes.

Methods, libraries, and kits for nucleotide sequencing are provided.