[HTML][HTML] Metabolomics and multi-omics integration: a survey of computational methods and resources

T Eicher, G Kinnebrew, A Patt, K Spencer, K Ying, Q Ma… - Metabolites, 2020‏ - mdpi.com
As researchers are increasingly able to collect data on a large scale from multiple clinical
and omics modalities, multi-omics integration is becoming a critical component of …

Avoiding common pitfalls when clustering biological data

T Ronan, Z Qi, KM Naegle - Science signaling, 2016‏ - science.org
Clustering is an unsupervised learning method, which groups data points based on
similarity, and is used to reveal the underlying structure of data. This computational …

[HTML][HTML] A deep learning approach to antibiotic discovery

JM Stokes, K Yang, K Swanson, W **, A Cubillos-Ruiz… - Cell, 2020‏ - cell.com
Due to the rapid emergence of antibiotic-resistant bacteria, there is a growing need to
discover new antibiotics. To address this challenge, we trained a deep neural network …

[ספר][B] Practical multivariate analysis

A Afifi, S May, R Donatello, VA Clark - 2019‏ - taylorfrancis.com
This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its
practical and accessible approach, with excellent examples and good guidance on …

A systematic comparative evaluation of biclustering techniques

VA Padilha, RJGB Campello - BMC bioinformatics, 2017‏ - Springer
Background Biclustering techniques are capable of simultaneously clustering rows and
columns of a data matrix. These techniques became very popular for the analysis of gene …

Population structure discovery in meta-analyzed microbial communities and inflammatory bowel disease using MMUPHin

S Ma, D Shungin, H Mallick, M Schirmer, LH Nguyen… - Genome biology, 2022‏ - Springer
Microbiome studies of inflammatory bowel diseases (IBD) have achieved a scale for meta-
analysis of dysbioses among populations. To enable microbial community meta-analyses …

Characterisation of cell lines derived from prostate cancer patients with localised disease

L Moya, C Walpole, F Rae, S Srinivasan… - Prostate Cancer and …, 2023‏ - nature.com
Background Prostate cancer is a broad-spectrum disease, spanning from indolent to a
highly aggressive lethal malignancy. Prostate cancer cell lines are essential tools to …

Toward kingdom-wide analyses of gene expression

I Julca, QW Tan, M Mutwil - Trends in Plant Science, 2023‏ - cell.com
Gene expression data for Archaeplastida are accumulating exponentially, with more than
300 000 RNA-sequencing (RNA-seq) experiments available for hundreds of species. The …

Hyperbolic diffusion embedding and distance for hierarchical representation learning

YWE Lin, RR Coifman, G Mishne… - … on Machine Learning, 2023‏ - proceedings.mlr.press
Finding meaningful representations and distances of hierarchical data is important in many
fields. This paper presents a new method for hierarchical data embedding and distance. Our …

Heterogeneous data integration methods for patient similarity networks

J Gliozzo, M Mesiti, M Notaro, A Petrini… - Briefings in …, 2022‏ - academic.oup.com
Patient similarity networks (PSNs), where patients are represented as nodes and their
similarities as weighted edges, are being increasingly used in clinical research. These …