Abstract: In accordance with embodiments, a computing device of a processing system performs a seed search of a short read (SR) against a reference sequence using a Burrows Wheeler Transform (BWT) algorithm to determine a seed. During the seed search one or more seed candidates in the reference sequence are determined. If the number of matches is less than or equal to a predefined threshold value the seed search using the BWT algorithm is stopped. Each seed candidate is extended to a respective extended seed candidate equal in length to the SR. bp-to-bp comparisons are performed between a remaining bp sequence of the SR after the matching bp and a corresponding remaining bp sequence in each extended seed candidate. An extended seed candidate that exactly matches the SR in the bp-to-bp comparisons is outputted as the seed.

Abstract: The present invention provide a method of constructing a ligand-receptor protein complex to determine the binding activity of different PBDEs derivatives to an enoyl-ACP reductase. The method comprises providing a ligand-receptor binding complex, molecular docking and performing molecular dynamic simulation. The present invention is able to determine the binding activity of PBDEs derivatives to the enoyl-ACP reductase comparable to the results obtained in vitro.

Abstract: Methods and systems for processing a plurality of sample reads for genome sequencing include, for each sample read of the plurality of sample reads, comparing substring sequences from the sample read to reference sequences representing different portions of a reference genome. One or more reference sequences are identified that match one or more of the compared substring sequences, and a probabilistic location within the reference genome is determined for the sample read based on the one or more identified reference sequences. The reference genome is partitioned for reference-aligned genome sequencing based on the determined probabilistic locations of the respective sample reads.

Abstract: The present invention provides a powerful tool to identify personalized therapeutic strategies. In particular, the invention provides methods for determining therapeutically targetable dominant signaling pathways in a cancer sample from a subject affected with a solid cancer, determining a treatment protocol for the subject, selecting a subject for a therapy, determining whether the subject is susceptible to benefit from a therapy, predicting clinical outcome of the subject, treating the subject and/or predicting the sensitivity of a solid cancer to a therapy.

Abstract: Technologies are provided for an improved classifier apparatus and processes for improving the accuracy of classification technology including example applications of such classifiers. A process includes applying clustering to variables contributing to the classification task. The clusters may be represented in a 1-dimensional, 2-dimensional, or 3-dimensional matrix that is a spatial abstraction of the interrelationships. A convolutional transformation may be applied to the matrix so as to reduce the effective dimensionality of the classification problem and improve the signal-to-noise ration. A deep learning neural network method may be applied to the transformed network to generate an improved classification model, which may be utilized by a decision support tool. One embodiment comprises a decision support tool for detecting risk of venous thrombosis and venous thromboembolism (VTE) in a patient, based on phenotype and genomics information.