AIMC Topic: Mutation

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Unified rational protein engineering with sequence-based deep representation learning.

Nature methods
Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically...

One-shot optimization of multiple enzyme parameters: Tailoring glucose oxidase for pH and electron mediators.

Biotechnology and bioengineering
Enzymes are biological catalysts with many industrial applications, but natural enzymes are usually unsuitable for industrial processes because they are not optimized for the process conditions. The properties of enzymes can be improved by directed e...

Predicting the 1p/19q Codeletion Status of Presumed Low-Grade Glioma with an Externally Validated Machine Learning Algorithm.

Clinical cancer research : an official journal of the American Association for Cancer Research
PURPOSE: Patients with 1p/19q codeleted low-grade glioma (LGG) have longer overall survival and better treatment response than patients with 1p/19q intact tumors. Therefore, it is relevant to know the 1p/19q status. To investigate whether the 1p/19q ...

Predicting CRISPR/Cas9-Induced Mutations for Precise Genome Editing.

Trends in biotechnology
SpCas9 creates blunt end cuts in the genome and generates random and unpredictable mutations through error-prone repair systems. However, a growing body of recent evidence points instead to Cas9-induced staggered end generation, nonrandomness of muta...

[Coexistence of mycosis fungoides and essential thrombocythemia with JAK2V617F].

Revista medica del Instituto Mexicano del Seguro Social
BACKGROUND: The coexistence of myeloproliferative neoplasms (MPNs), specifically essential thrombocythemia and lymphoproliferative neoplasms, are a very rare finding with a frequency < 1%.

Prediction of melanoma evolution in melanocytic nevi via artificial intelligence: A call for prospective data.

European journal of cancer (Oxford, England : 1990)
Recent research revealed the superiority of artificial intelligence over dermatologists to diagnose melanoma from images. However, 30-50% of all melanomas and more than half of those in young patients evolve from initially benign lesions. Despite its...

Cross-registry neural domain adaptation to extract mutational test results from pathology reports.

Journal of biomedical informatics
OBJECTIVE: We study the performance of machine learning (ML) methods, including neural networks (NNs), to extract mutational test results from pathology reports collected by cancer registries. Given the lack of hand-labeled datasets for mutational te...

Artificial Intelligence Approach to Find Lead Compounds for Treating Tumors.

The journal of physical chemistry letters
It has been demonstrated that MMP13 enzyme is related to most cancer cell tumors. The world's largest traditional Chinese medicine database was applied to screen for structure-based drug design and ligand-based drug design. To predict drug activity, ...

CT texture analysis for the prediction of KRAS mutation status in colorectal cancer via a machine learning approach.

European journal of radiology
PURPOSE: This study aimed to investigate whether a machine learning-based computed tomography (CT) texture analysis could predict the mutation status of V-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog (KRAS) in colorectal cancer.