11 citations · 25 across the 9 of their papers we have counts for
9 papers
On Separate Normalization in Self-supervised Transformers
Xiaohui Chen, Yinkai Wang, Yuanqi Du +2
Self-supervised training methods for transformers have demonstrated remarkable performance across various domains. Previous transformer-based models, such as masked autoencoders (M…
Ensemble Spectral Prediction (ESP) Model for Metabolite Annotation
Xinmeng Li, Hao Zhu, Li-ping Liu +1
A key challenge in metabolomics is annotating measured spectra from a biological sample with chemical identities. Currently, only a small fraction of measurements can be assigned i…
Boost-RS: Boosted Embeddings for Recommender Systems and its Application to Enzyme-Substrate Interaction Prediction
Xinmeng Li, Li-ping Liu, Soha Hassoun
Despite experimental and curation efforts, the extent of enzyme promiscuity on substrates continues to be largely unexplored and under documented. Recommender systems (RS), which a…
Stochastic Iterative Graph Matching
Linfeng Liu, Michael C. Hughes, Soha Hassoun +1
Recent works leveraging Graph Neural Networks to approach graph matching tasks have shown promising results. Recent progress in learning discrete distributions poses new opportunit…
Using Graph Neural Networks for Mass Spectrometry Prediction
Hao Zhu, Liping Liu, Soha Hassoun
Detecting and quantifying products of cellular metabolism using Mass Spectrometry (MS) has already shown great promise in many biological and biomedical applications. The biggest c…
ASAP-SML: An Antibody Sequence Analysis Pipeline Using Statistical Testing and Machine Learning
Xinmeng Li, James A. Van Deventer, Soha Hassoun
Antibodies are capable of potently and specifically binding individual antigens and, in some cases, disrupting their functions. The key challenge in generating antibody-based inhib…
Learning graph representations of biochemical networks and its application to enzymatic link prediction
Julie Jiang, Li-Ping Liu, Soha Hassoun
The complete characterization of enzymatic activities between molecules remains incomplete, hindering biological engineering and limiting biological discovery. We develop in this w…
Enzyme promiscuity prediction using hierarchy-informed multi-label classification
Gian Marco Visani, Michael C. Hughes, Soha Hassoun
As experimental efforts are costly and time consuming, computational characterization of enzyme capabilities is an attractive alternative. We present and evaluate several machine-l…
Pathway-Activity Likelihood Analysis and Metabolite Annotation for Untargeted Metabolomics using Probabilistic Modeling
Ramtin Hosseini, Neda Hassanpour, Li-Ping Liu +1
Motivation: Untargeted metabolomics comprehensively characterizes small molecules and elucidates activities of biochemical pathways within a biological sample. Despite computationa…