Search Results for "gene"

Scanpy is a scalable toolkit for analyzing single-cell gene expression data built jointly with anndata. It includes preprocessing, visualization, clustering, trajectory inference and differential expression testing. The Python-based implementation efficiently deals with datasets of more than one million cells.

...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.

Geroes is a deep learning-based system dedicated to evaluating gene contribution in defining tissue specificity.

The source code has been migrated and is now hosted on Github: https://github.com/jenetics/jenetics Jenetics is an advanced Genetic Algorithm, Evolutionary Algorithm and Genetic Programming library, respectively, written in modern day Java. It is designed with a clear separation of the several algorithm concepts, e. g. Gene, Chromosome, Genotype, Phenotype, Population and fitness Function. Jenetics allows you to minimize or maximize the given fitness function without tweaking it. In contrast to other GA implementations, the library uses the concept of an evolution stream (EvolutionStream) for executing the evolution steps. Since the EvolutionStream implements the Java Stream interface, it works smoothly with the rest of the Java Stream API. ...

This repository is home to the Deep Review, a review article on deep learning in precision medicine. The Deep Review is collaboratively written on GitHub using a tool called Manubot (see below). The project operates on an open contribution model, welcoming contributions from anyone. To see what's incoming, check the open pull requests. For project discussion and planning see the Issues. As of writing, we are aiming to publish an update of the deep review. We will continue to make project...

GNAT is a BioNLP/text mining tool to recognize and identify gene/protein names in natural language text. It will detect mentions of genes in text, such as PubMed/Medline abstracts, and disambiguate them to remove false positives and map them to the correct entry in the NCBI Entrez Gene database by gene ID. March 2017: We started to upload GNAT output on Medline. See files/results/medline/.

LiveGMS is a PHP/MySQL driven gene editor for the game Creatures 3 / Docking Station. It provides a platform independent online editor with most features other binary genetics editors have.

...The genetic algorithm engine supports various mutation rates, ranked parental selection, stochastic sampling parental selection, cyclic crossover, crossover at each gene, cloning the best individual each generation, and creating random individuals each generation. To use the genetic algorithm engine to search for a different problem's solution, one needs to program a fitness function, the project settings, and a few virtual functions.

The BioNLP UIMA Component Repository provides UIMA wrappers for novel and well-known 3rd-party NLP tools used in biomedical text prosessing, such as tokenizers, parsers, named entity taggers, and tools for evaluation.

BIL++ is a set of standalone C++ packages for data processing in Bioinformatics (Graph mining, Bayesian networks, Genetic algorithm, Discretization, Gene expression data analysis, Hypothesis testing).

Moara is a biological text mining tool and consists of a Java library and some auxiliary MySQL databases for gene/protein training and extraction of mentions and its further normalization and disambiguation.

This is C++ application code that implements Gene Expression Programming, or GEP - a form of genetic algorithm.

GEP is an evolutionary algorithm for function finding. This framework is a powerful way of expressing and coding genetic-like structures and quickly finding solutions through evolution by common genetic operators.

The Gene Expression Programming Framework in Java. It separates the process of evolution from the process of interpretation of the chromosome, allowing the use of various schemes in the chromosome.

Conrad is both a high performance Conditional Random Field engine which can be applied to a variety of machine learning problems and a specific set of models for gene prediction using semi-Markov CRFs.

Jeep is a modular, abstract and distributed evolutionnary programming core written in Java, allowing to grow autonomous agents as well a gene pool (as in genetic algorithms).