A platform configured to predict type or family of an unknown drug candidate compound, the platform including: a living cell or a tissue; a detector that measures an indicator of a cellular response by the living cell or tissue upon exposure to the unknown drug candidate compound; a memory configured to store data related to the indicator of the cellular response detected by the detector from a library of drug types and/or families; and one or more processing unit(s) configured to: process the data related to the indicator of the cellular response of the living cell or tissue upon exposure to the unknown drug candidate compound, and compare cellular response data from the library of drug types and/or families, so that a drug type and/or a drug family and/or a mechanism of action of the unknown drug candidate compound can be predicted on the basis of a similarity between the detected cellular response data of the unknown drug candidate compound and the cellular response data of the library of drug types and/or families. Also disclosed are methods of screening an unknown drug, including: comparing the data measured from a test cell to corresponding cellular response data in a library of known drug types, and determining a relationship between the unknown drug and a known drug type or a known drug family to predict the type or family of the unknown drug.

Monitoring, analysis and control of fermentation activities includes methods and corresponding systems directed toward agriculture, biofuels, and food production. Complex methods and corresponding systems are provided for classifying a microorganism; profiling a microbiome; sequencing multiple libraries in a single sequencing run; determining a microbiome profile in a sample; and analyzing a material from a location associated with a fermentation process. Additional implementations are directed to methods and corresponding systems for obtaining, deriving, predicting and evaluating microbiome information; control, analysis and direction of fermentation operations; and evaluating, analyzing and displaying microbiome related information in two and three dimensional plots. Yet additional methods and corresponding systems permit identification and analysis of microorganisms capable of imparting beneficial properties to phases of fermentation processes.

Described herein are methods of identifying a plurality of polynucleotides, as well as detecting presence, absence, or abundance of a plurality of taxa in a sample. Also provided are systems for performing methods of the disclosure.

Disclosed herein are system, method, and computer program product embodiments for determining phenotypic impacts of molecular variants identified within a biological sample. Embodiments include receiving molecular variants associated with functional elements within a model system. The embodiments then determine molecular scores associated with the model system. The embodiments then determine molecular signals and population signals associated with the molecular variants based on the molecular scores. The embodiments then determine functional scores for the molecular variants based on statistical learning. The embodiments then derive evidence scores of the molecular variants based on the functional scores. The embodiments then determine phenotypic impacts of the molecular variants based on the functional scores or evidence scores.

The invention relates to prenatal detection methods using non-invasive techniques. In particular, it relates to prenatal diagnosis of a fetal chromosomal aneuploidy by detecting fetal and maternal nucleic acids in a maternal biological sample. More particularly, the invention applies multiplex PCR to amplify selected fractions of the respective chromosomes of maternal and fetal chromosomes. Respective amounts of suspected aneuploid chromosomal regions and reference chromosomes are determined from massive sequencing analysis followed by a statistical analysis to detect a particular aneuploidy.

Embodiments of the present invention are directed to a computer-implemented method for positive OTU identification. A non-limiting example of the computer-implemented method includes receiving, by a processor, a plurality of sequencing reads for a metagenome sample and, for each of the plurality of sequencing reads, a corresponding OTU set comprising a plurality of OTUs. The method also includes determining, by the processor, a true positive score for each of the plurality of OTUs based upon a ech Complex and generating a plurality of preliminary OTUs. The method also includes determining a threshold score for the preliminary OTUs. The method also includes removing one of the preliminary OTUs based at least in part upon a determination that the true positive score is less than a threshold. The method also includes retaining one of the preliminary OTUs based at least in part upon a determination that the true positive score is greater than or equal to the threshold.

Embodiments of the present invention are directed to a computer-implemented method for positive OTU identification. A non-limiting example of the computer-implemented method includes receiving, by a processor, a plurality of sequencing reads for a metagenome sample and, for each of the plurality of sequencing reads, a corresponding OTU set comprising a plurality of OTUs. The method also includes determining, by the processor, a true positive score for each of the plurality of OTUs based upon a Cech Complex and generating a plurality of preliminary OTUs. The method also includes determining a threshold score for the preliminary OTUs. The method also includes removing one of the preliminary OTUs based at least in part upon a determination that the true positive score is less than a threshold. The method also includes retaining one of the preliminary OTUs based at least in part upon a determination that the true positive score is greater than or equal to the threshold.

The present invention relates to a method for discovery of a novel miRNA biomarker for cancer diagnosis, a biomarker for diagnosis of bile duct cancer or pancreatic cancer which has been discovered through the method for discovery of a biomarker, a method for diagnosing cancer, comprising a step in which cancer is diagnosed when f(x)>0 by substitution of the expression level of the miRNA biomarker, which is detected by the method for discovery of a miRNA biomarker for cancer diagnosis, in a sample into a novel SVM classifier function, a kit for diagnosing bile duct cancer or pancreatic cancer comprising the biomarker for diagnosing bile duct cancer or pancreatic cancer, and a computing device for performing a process of diagnosing cancer when f(x)>0 as a result of a calculation by substitution of the expression level of a miRNA biomarker, which is detected by the method for discovery of a miRNA biomarker for cancer diagnosis, into the novel SVM classifier function.

A method for annotating a protein sequence or a subsequence thereof includes the steps of providing an input protein sequence or a subsequence thereof. The subsequence is defined as a central node of a graph or protein network. A subgraph of the graph is calculated including the central node, according to a predefined radius and weights and/or resistances of edges of the subgraph are also calculated. Annotated nodes in the subgraph are identified. Resistance values between the central nodes and each of the annotated nodes in the subgraph are calculated and a list of annotated nodes is outputted. Each of the annotated nodes has a characteristic calculated resistance value to the central node of the input protein sequence.

A system configured to characterize a number of contributors to a DNA mixture within a sample, the system comprising: a sample preparation module configured to generate initial data about the DNA mixture within the sample; a processor comprising a number of contributors determination module comprising a machine-learning algorithm configured to: (i) receive the generated initial data; (ii) analyze the generated initial data to determine the number of contributors to the DNA mixture within the sample; and an output device configured to receive the determined number of contributors from the processor, and further configured output information about the received determined number of contributors.