6 papers
GBNL: Graded Betti Number Learning of Complex Biological Data
Mushal Zia, Faisal Suwayyid, Guo-Wei Wei
While persistent homology is widely used for data shape analysis, persistent commutative algebra (PCA) has seen limited adoption in machine learning and data science. Unlike persis…
CAP: Commutative Algebra Prediction of Protein-Nucleic Acid Binding Affinities
Mushal Zia, Faisal Suwayyid, Yuta Hozumi +3
An accurate prediction of protein-nucleic acid binding affinity is vital for deciphering genomic processes, yet existing approaches often struggle in reconciling high accuracy with…
Commutative algebra neural network reveals genetic origins of diseases
JunJie Wee, Faisal Suwayyid, Mushal Zia +3
Genetic mutations can disrupt protein structure, stability, and solubility, contributing to a wide range of diseases. Existing predictive models often lack interpretability and fai…
Topological Sequence Analysis of Genomes: Category theory Approaches
Jian Liu, Li Shen, Mushal Zia +1
Sequence data, such as DNA, RNA, and protein sequences, exhibit intricate, multi-scale structures that pose significant challenges for conventional analysis methods, particularly t…
CAML: Commutative algebra machine learning -- a case study on protein-ligand binding affinity prediction
Hongsong Feng, Faisal Suwayyid, Mushal Zia +4
Recently, Suwayyid and Wei have introduced commutative algebra as an emerging paradigm for machine learning and data science. In this work, we integrate commutative algebra machine…
Persistent Directed Flag Laplacian (PDFL)-Based Machine Learning for Protein-Ligand Binding Affinity Prediction
Mushal Zia, Benjamin Jones, Hongsong Feng +1
Directionality in molecular and biomolecular networks plays a significant role in the accurate represention of the complex, dynamic, and asymmetrical nature of interactions present…