Explainable artificial intelligence for omics data: a systematic mapping study
Researchers increasingly turn to explainable artificial intelligence (XAI) to analyze omics
data and gain insights into the underlying biological processes. Yet, given the …
data and gain insights into the underlying biological processes. Yet, given the …
Application of biological domain knowledge based feature selection on gene expression data
In the last two decades, there have been massive advancements in high throughput
technologies, which resulted in the exponential growth of public repositories of gene …
technologies, which resulted in the exponential growth of public repositories of gene …
Alfalfa yield prediction using UAV-based hyperspectral imagery and ensemble learning
Alfalfa is a valuable and intensively produced forage crop in the United States, and the
timely estimation of its yield can inform precision management decisions. However …
timely estimation of its yield can inform precision management decisions. However …
Prediction of sediment heavy metal at the Australian Bays using newly developed hybrid artificial intelligence models
Hybrid artificial intelligence (AI) models are developed for sediment lead (Pb) prediction in
two Bays (ie, Bramble (BB) and Deception (DB)) stations, Australia. A feature selection (FS) …
two Bays (ie, Bramble (BB) and Deception (DB)) stations, Australia. A feature selection (FS) …
Explaining decisions of graph convolutional neural networks: patient-specific molecular subnetworks responsible for metastasis prediction in breast cancer
H Chereda, A Bleckmann, K Menck, J Perera-Bel… - Genome medicine, 2021 - Springer
Background Contemporary deep learning approaches show cutting-edge performance in a
variety of complex prediction tasks. Nonetheless, the application of deep learning in …
variety of complex prediction tasks. Nonetheless, the application of deep learning in …
Google goes cancer: improving outcome prediction for cancer patients by network-based ranking of marker genes
Predicting the clinical outcome of cancer patients based on the expression of marker genes
in their tumors has received increasing interest in the past decade. Accurate predictors of …
in their tumors has received increasing interest in the past decade. Accurate predictors of …
Insights into multimodal imaging classification of ADHD
Attention deficit hyperactivity disorder (ADHD) currently is diagnosed in children by
clinicians via subjective ADHD-specific behavioral instruments and by reports from the …
clinicians via subjective ADHD-specific behavioral instruments and by reports from the …
Pathway-based genomics prediction using generalized elastic net
We present a novel regularization scheme called The Generalized Elastic Net (GELnet) that
incorporates gene pathway information into feature selection. The proposed formulation is …
incorporates gene pathway information into feature selection. The proposed formulation is …
Revealing shared and distinct genes responding to JA and SA signaling in Arabidopsis by meta-analysis
N Zhang, S Zhou, D Yang, Z Fan - Frontiers in plant science, 2020 - frontiersin.org
Plant resistance against biotrophic and necrotrophic pathogens is mediated by mutually
synergistic and antagonistic effects of salicylic acid (SA) and jasmonic acid (JA) signals …
synergistic and antagonistic effects of salicylic acid (SA) and jasmonic acid (JA) signals …
Classification and gene selection of triple-negative breast cancer subtype embedding gene connectivity matrix in deep neural network
J Liu, R Su, J Zhang, L Wei - Briefings in Bioinformatics, 2021 - academic.oup.com
Triple-negative breast cancer (TNBC) has been a challenging breast cancer subtype for
oncological therapy. Normally, it can be classified into different molecular subtypes …
oncological therapy. Normally, it can be classified into different molecular subtypes …