AIMC Topic: Bacteria
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Artificial Intelligence Techniques to Computational Proteomics, Genomics, and Biological Sequence Analysis.
Current protein & peptide science
Jan 1, 2020
In vitro cytotoxic, antioxidant, antibacterial and antifungal activity of Saussurea heteromalla indigenous to Pakistan.
Pakistan journal of pharmaceutical sciences
Nov 1, 2019
Medicinal plants are proven to reveal vast promising potential providing novel drug candidates to combat health-related problems. The aim of current study is to discover new drug compounds with anti-anticancer, antioxidant, antibacterial and antifung...
Microfluidic cap-to-dispense (μCD): a universal microfluidic-robotic interface for automated pipette-free high-precision liquid handling.
Lab on a chip
Oct 9, 2019
Microfluidic devices have been increasingly used for low-volume liquid handling operations. However, laboratory automation of such delicate devices has lagged behind due to the lack of world-to-chip (macro-to-micro) interfaces. In this paper, we have...
BacPaCS-Bacterial Pathogenicity Classification via Sparse-SVM.
Bioinformatics (Oxford, England)
Jun 1, 2019
MOTIVATION: Bacterial infections are a major cause of illness worldwide. However, most bacterial strains pose no threat to human health and may even be beneficial. Thus, developing powerful diagnostic bioinformatic tools that differentiate pathogenic...
The Gene Ontology Resource: 20 years and still GOing strong.
Nucleic acids research
Jan 8, 2019
The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under cont...
Learned protein embeddings for machine learning.
Bioinformatics (Oxford, England)
Aug 1, 2018
MOTIVATION: Machine-learning models trained on protein sequences and their measured functions can infer biological properties of unseen sequences without requiring an understanding of the underlying physical or biological mechanisms. Such models enab...
Cost function network-based design of protein-protein interactions: predicting changes in binding affinity.
Bioinformatics (Oxford, England)
Aug 1, 2018
MOTIVATION: Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of proteins for a wide range of applications. Free energy is defined by enthalpic and entropic contributi...
An mRMR-SVM Approach for Opto-Fluidic Microorganism Classification.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2018
The detection of microorganisms is important in numerous applications such as water quality monitoring, blood analysis, and food testing. The conventional detection methods are tedious and labour-intensive. Establish methods involve culturing, counti...
DeepSig: deep learning improves signal peptide detection in proteins.
Bioinformatics (Oxford, England)
May 15, 2018
MOTIVATION: The identification of signal peptides in protein sequences is an important step toward protein localization and function characterization.
DeepGO: predicting protein functions from sequence and interactions using a deep ontology-aware classifier.
Bioinformatics (Oxford, England)
Feb 15, 2018
MOTIVATION: A large number of protein sequences are becoming available through the application of novel high-throughput sequencing technologies. Experimental functional characterization of these proteins is time-consuming and expensive, and is often ...
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