Genetics

Predictable and precise template-free CRISPR editing of pathogenic variants.

Following Cas9 cleavage, DNA repair without a donor template is generally considered stochastic, heterogeneous and impractical beyond gene disruption. Here, we show that template-free Cas9 editing is predictable and capable of precise repair to a predicted genotype, enabling correction of disease-associated mutations in humans. We constructed a library of 2,000 Cas9 guide RNAs paired with DNA targ...

Vibrational Properties of Metastable Polymorph Structures by Machine Learning.

Despite vibrational properties being critical for the ab initio prediction of finite-temperature stability as well as thermal conductivity and other transport properties of solids, their inclusion in ab initio materials repositories has been hindered by expensive computational requirements. Here we tackle the challenge, by showing that a good estimation of force constants and vibrational propertie...

Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.

Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual pat...

In Silico Prediction of O⁶-Methylguanine-DNA Methyltransferase Inhibitory Potency of Base Analogs with QSAR and Machine Learning Methods.

O⁶-methylguanine-DNA methyltransferase (MGMT), a unique DNA repair enzyme, can confer resistance to DNA anticancer alkylating agents that modify the O...

Introducing Heuristic Information Into Ant Colony Optimization Algorithm for Identifying Epistasis.

Epistasis learning, which is aimed at detecting associations between multiple Single Nucleotide Polymorphisms (SNPs) and complex diseases, has gained ...

Anti-microbial and anti-mycotoxigenic activities of endophytic isolated from (L.) G. Don.: molecular characterisation and bioactive compound isolation.

The present study investigated the anti-microbial and anti-mycotoxigenic activities of the ethyl acetate extract (EA) and a bioactive compound obtaine...

Nucleotide and structural label identification in single RNA molecules with quantum tunneling spectroscopy.

Although a number of advances have been made in RNA sequencing and structural characterization, the lack of a method for directly determining the sequ...

A deep learning approach to automate refinement of somatic variant calling from cancer sequencing data.

Cancer genomic analysis requires accurate identification of somatic variants in sequencing data. Manual review to refine somatic variant calls is requ...

Generalized multifactor dimensionality reduction approaches to identification of genetic interactions underlying ordinal traits.

The manifestation of complex traits is influenced by gene-gene and gene-environment interactions, and the identification of multifactor interactions i...

On String Languages Generated by Spiking Neural P Systems With Structural Plasticity.

Spiking neural P systems (SNP systems) are parallel and non-deterministic models of computation, inspired by the neural system of the brain. A variant...

LogLoss-BERAF: An ensemble-based machine learning model for constructing highly accurate diagnostic sets of methylation sites accounting for heterogeneity in prostate cancer.

Although modern methods of whole genome DNA methylation analysis have a wide range of applications, they are not suitable for clinical diagnostics due...

Effective feature learning and fusion of multimodality data using stage-wise deep neural network for dementia diagnosis.

In this article, the authors aim to maximally utilize multimodality neuroimaging and genetic data for identifying Alzheimer's disease (AD) and its pro...

Biohydrogen production under hyper salinity stress by an anaerobic sequencing batch reactor with mixed culture.

BACKGROUND: This study investigated the effect of organic loading rate (OLR) and NaCl concentration on biohydrogen production by preheated anaerobic s...

Large-Scale Multi-Class Image-Based Cell Classification With Deep Learning.

Recent advances in ultra-high-throughput microscopy have enabled a new generation of cell classification methodologies using image-based cell phenotyp...

Gene Essentiality Analyzed by Transposon Mutagenesis and Machine Learning in a Stable Haploid Isolate of .

Knowing the full set of essential genes for a given organism provides important information about ways to promote, and to limit, its growth and surviv...

Role of Electrostatic Interactions on Supramolecular Organization in Calf-Thymus DNA Solutions under Flow.

Previous investigations were conducted on two concentrations of DNA solution: 4 mg/mL, for which it has been shown that no supramolecular organization...

Automated detection of cancer cells in effusion specimens by DNA karyometry.

BACKGROUND: The average sensitivity of conventional cytology for the identification of cancer cells in effusion specimens is only approximately 58%. D...

Ensemble of machine learning algorithms using the stacked generalization approach to estimate the warfarin dose.

Warfarin dosing remains challenging due to narrow therapeutic index and highly individual variability. Incorrect warfarin dosing is associated with de...

Drug Repurposing Prediction for Immune-Mediated Cutaneous Diseases using a Word-Embedding-Based Machine Learning Approach.

Immune-mediated diseases affect more than 20% of the population, and many autoimmune diseases affect the skin. Drug repurposing (or repositioning) is ...

Machine learning and structural analysis of Mycobacterium tuberculosis pan-genome identifies genetic signatures of antibiotic resistance.

Mycobacterium tuberculosis is a serious human pathogen threat exhibiting complex evolution of antimicrobial resistance (AMR). Accordingly, the many pu...