AIMC Topic: Computational Biology

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A Cancer Biologist's Primer on Machine Learning Applications in High-Dimensional Cytometry.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
The application of machine learning and artificial intelligence to high-dimensional cytometry data sets has increasingly become a staple of bioinformatic data analysis over the past decade. This is especially true in the field of cancer biology, wher...

Computational inference of cancer-specific vulnerabilities in clinical samples.

Genome biology
BACKGROUND: Systematic in vitro loss-of-function screens provide valuable resources that can facilitate the discovery of drugs targeting cancer vulnerabilities.

Concise Polygenic Models for Cancer-Specific Identification of Drug-Sensitive Tumors from Their Multi-Omics Profiles.

Biomolecules
In silico models to predict which tumors will respond to a given drug are necessary for Precision Oncology. However, predictive models are only available for a handful of cases (each case being a given drug acting on tumors of a specific cancer type)...

Predicting protein subcellular location with network embedding and enrichment features.

Biochimica et biophysica acta. Proteins and proteomics
The subcellular location of a protein is highly related to its function. Identifying the location of a given protein is an essential step for investigating its related problems. Traditional experimental methods can produce solid determination. Howeve...

Prognostic prediction of carcinoma by a differential-regulatory-network-embedded deep neural network.

Computational biology and chemistry
The accurate prognostic prediction is essential for precise diagnosis and treatment of carcinoma. In addition to clinical survival prediction method, many computational methods based on transcriptomic data have been proposed to build the prediction m...

Precise automatic classification of 46 different pollen types with convolutional neural networks.

PloS one
In palynology, the visual classification of pollen grains from different species is a hard task which is usually tackled by human operators using microscopes. Many industries, including medical and pharmaceutical, rely on the accuracy of this manual ...

CoRNeA: A Pipeline to Decrypt the Inter-Protein Interfaces from Amino Acid Sequence Information.

Biomolecules
Decrypting the interface residues of the protein complexes provides insight into the functions of the proteins and, hence, the overall cellular machinery. Computational methods have been devised in the past to predict the interface residues using ami...

Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Nucleosides, nucleotides & nucleic acids
Hereditary disease prediction in eukaryotic DNA using signal processing approaches is an incredible work in bioinformatics. Researchers of various fields are trying to put forth a noninvasive approach to forecast the disease-related genes. As disease...