AIMC Topic: Biological Products

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Unlocking plant bioactive pathways: omics data harnessing and machine learning assisting.

Current opinion in biotechnology
Plant bioactives hold immense potential in the medicine and food industry. The recent advancements in omics applied in deciphering specialized metabolic pathways underscore the importance of high-quality genome releases and the wealth of data in meta...

PECAN Predicts Patterns of Cancer Cell Cytostatic Activity of Natural Products Using Deep Learning.

Journal of natural products
Many machine learning techniques are used as drug discovery tools with the intent to speed characterization by determining relationships between compound structure and biological function. However, particularly in anticancer drug discovery, these mod...

Pain-free oral delivery of biologic drugs using intestinal peristalsis-actuated microneedle robots.

Science advances
Biologic drugs hold immense promise for medical treatments, but their oral delivery remains a daunting challenge due to the harsh digestive environment and restricted gastrointestinal absorption. Here, inspired by the porcupinefish's ability to infla...

Prospective Antiviral Effect of Aqueous Extract against COVID-19 Infection.

Marine drugs
Marine algal extracts exhibit a potent inhibitory effect against several enveloped and non-enveloped viruses. The infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has several adverse effects, including an increased mortality ...

APOLLO 11 Project, Consortium in Advanced Lung Cancer Patients Treated With Innovative Therapies: Integration of Real-World Data and Translational Research.

Clinical lung cancer
INTRODUCTION: Despite several therapeutic efforts, lung cancer remains a highly lethal disease. Novel therapeutic approaches encompass immune-checkpoint inhibitors, targeted therapeutics and antibody-drug conjugates, with different results. Several s...

Bioactive Molecules from the Innate Immunity of Ascidians and Innovative Methods of Drug Discovery: A Computational Approach Based on Artificial Intelligence.

Marine drugs
The study of bioactive molecules of marine origin has created an important bridge between biological knowledge and its applications in biotechnology and biomedicine. Current studies in different research fields, such as biomedicine, aim to discover m...

Computational prediction of complex cationic rearrangement outcomes.

Nature
Recent years have seen revived interest in computer-assisted organic synthesis. The use of reaction- and neural-network algorithms that can plan multistep synthetic pathways have revolutionized this field, including examples leading to advanced natur...

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

European journal of nuclear medicine and molecular imaging
PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pu...

Artificial intelligence for natural product drug discovery.

Nature reviews. Drug discovery
Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have le...

Virtual screening strategy for anti-DPP-IV natural flavonoid derivatives based on machine learning.

Journal of biomolecular structure & dynamics
Flavonoids, especially their inhibitory effect on DPP-IV activity, have been widely recognized for their antidiabetic effects. However, the variety of natural flavonoid derivatives is very rich, and even subtle structural differences can lead to seve...