Search Results for "patterns"

...This repository contains client-side code, examples, and documentation to help you use the AlphaGenome API. AlphaGenome offers multimodal predictions, encompassing diverse functional outputs such as gene expression, splicing patterns, chromatin features, and contact maps. The model analyzes DNA sequences of up to 1 million base pairs in length and can deliver predictions at single-base-pair resolution for most outputs. AlphaGenome achieves state-of-the-art performance across a range of genomic prediction benchmarks, including numerous diverse variant effect prediction tasks.

Croizat is a free, user-friendly, cross-platform desktop software package which biologists can use to integrate and analyze spatial data on species or other taxa and to explore geographical patterns in diversity under a panbiogeographic and graph-theoretic approach.

...Allopolyploidy describes the formation of a new hybrid organism from the union of two or more different parents. Allopolyploid species carry multiple copies of each gene (homeologs), which often exhibit unusual expression patterns. Homeolog expression levels can technically be determined from next generation sequencing data (RNA-seq), but in practice, assigning reads to one homeolog over another is extremely challenging, particularly on a whole-genome scale. HyLiTE automates this process, and allows gene expression patterns to be explored even in very complex allopolyploid species.

This advanced machine learning algorithm is a Michigan-style learning classifier system (LCS) developed to specialize in classification, prediction, data mining, and knowledge discovery tasks. Michigan-style LCS algorithms constitute a unique class of algorithms that distribute learned patterns over a collaborative population of of individually interpretable IF:THEN rules, allowing them to flexibly and effectively describe complex and diverse problem spaces. ExSTraCS was primarily developed to address problems in epidemiological data mining to identify complex patterns relating predictive attributes in noisy datasets to disease phenotypes of interest. ...

Given the peptides (T-cell epitopes) PolyCTLDesigner selects flanking sequences to optimize TAP-binding and joins resulting oligopeptides into a polyepitope in a way providing efficient liberation of potential epitopes by proteasomal and/or immunoproteasomal processing and minimizing the number of junctional epitopes. For constructing polyepitopes PolyCTLDesigner utilizes known amino acid patterns of proteasome cleavage and TAP-binding specificity. PolyCTLDesigner is also able to choose antigenic peptides covering selected HLA repertoire with desired redundancy rate. Given the antigen sequences PolyCTLDesigner is also able to select T-helper epitopes. For predicting T-cell epitopes it uses TEpredict.

Application to create 'electronic fluorescent pictographic' representations of gene expression patterns. Created at the Provart lab of the department of Cell & Systems Biology, University of Toronto.

Simple python code that produces color-coded quality plots based on fastq format read quality scores. Scores are averaged over binned read tile coordinates. Useful for spotting spatial quality patterns.

A library and associated applications for searching for patterns in protein structures and measuring geometric parameters.