Genetics

repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.

UNLABELLED: In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facilitate the studies of DNAs and nucleotides, we developed a Python package called representations of DNAs (repDNA) for generating the widely used feature...

Colored Traveling Salesman Problem.

The multiple traveling salesman problem (MTSP) is an important combinatorial optimization problem. It has been widely and successfully applied to the practical cases in which multiple traveling individuals (salesmen) share the common workspace (city set). However, it cannot represent some application problems where multiple traveling individuals not only have their own exclusive tasks but also sha...

Convex nonnegative matrix factorization with manifold regularization.

Nonnegative Matrix Factorization (NMF) has been extensively applied in many areas, including computer vision, pattern recognition, text mining, and si...

MetaVelvet-SL: an extension of the Velvet assembler to a de novo metagenomic assembler utilizing supervised learning.

The assembly of multiple genomes from mixed sequence reads is a bottleneck in metagenomic analysis. A single-genome assembly program (assembler) is no...

HyDRA: gene prioritization via hybrid distance-score rank aggregation.

UNLABELLED: Gene prioritization refers to a family of computational techniques for inferring disease genes through a set of training genes and careful...

Internal validation of the QIAamp DNA Investigator Kit, QIAamp 96 DNA Swab BioRobot Kit and the BioRobot Universal System for DNA extraction from reference and crime scene samples.

PseDNA-Pro: DNA-Binding Protein Identification by Combining Chou's PseAAC and Physicochemical Distance Transformation.

Identification of DNA-binding proteins is an important problem in biomedical research as DNA-binding proteins are crucial for various cellular process...

Robot-assisted gait training in a patient with hereditary spastic paraplegia.

Robot-assisted gait training has been investigated for restoring walking through activity-dependent neuroplasticity in persons with various neurologic...

Dealing with heterogeneous classification problem in the framework of multi-instance learning.

To deal with heterogeneous classification problem efficiently, each heterogeneous object was represented by a set of measurements obtained on differen...

Estimation of teaching-learning-based optimization primer design using regression analysis for different melting temperature calculations.

Primers plays important role in polymerase chain reaction (PCR) experiments, thus it is necessary to select characteristic primers. Unfortunately, man...

How to learn about gene function: text-mining or ontologies?

As the amount of genome information increases rapidly, there is a correspondingly greater need for methods that provide accurate and automated annotat...

Kernel methods for large-scale genomic data analysis.

Machine learning, particularly kernel methods, has been demonstrated as a promising new tool to tackle the challenges imposed by today's explosive dat...

Bridging scales in cancer progression: mapping genotype to phenotype using neural networks.

In this review we summarise our recent efforts in trying to understand the role of heterogeneity in cancer progression by using neural networks to cha...

Feature Selection and Classification of Electroencephalographic Signals: An Artificial Neural Network and Genetic Algorithm Based Approach.

Feature selection is an important step in many pattern recognition systems aiming to overcome the so-called curse of dimensionality. In this study, an...

Prediction of road traffic death rate using neural networks optimised by genetic algorithm.

Road traffic injuries (RTIs) are realised as a main cause of public health problems at global, regional and national levels. Therefore, prediction of ...

Forecasting viral evolution from phylogenetic trees

Viral mutation forecasting plays a key role in pandemic preparedness by enabling researchers to anticipate novel variants and design proactive interve...

When Genomic Masking Priors Fail to Transfer: Strong Variant Prediction, Weak Functional Generation

Bidirectional discrete diffusion model appears naturally suited to genomic modeling because it can reconstruct missing sequence from both flanks. We d...

Reflection-aware Generative Novel View Synthesis

We propose Ref-GeNVS, a training-free, reflection-aware method for generative novel view synthesis (NVS) in mirror scenes. Existing multi-view diffusi...

Interpretable Multiomics Machine Learning Identifies GSDMB-Associated Epigenetic Repression and Reduced Immune Activity in Metastatic Colorectal Cancer

Background: Colorectal cancer (CRC) is a major cause of cancer-related mortality, with distant metastasis strongly associated with poor clinical outco...

Global tree encoding of atlas-scale single-cell genomics

The rapid expansion of single-cell genomic datasets has led to the compilation of biological resources comprising hundreds of millions of cells across...