Biology subjects

Xue, N.

Publications and source records attributed to Xue, N..

4 recordsLinked to original sources

bioRxiv2024

Interpretable scRNA-seq Analysis with Intelligent Gene Selection

AO_SCPLOWBSTRACTC_SCPLOWSingle-cell RNA sequencing (scRNA-seq) data analysis faces multiple challenges, including high dimensionality, significant noise, and data loss. To effectively address these issues, we introduce AIGS, a robust and transparent single-cell analysis framework. AIGS utilizes an intelligent gene selection method that systematically identifies the most informative genes for clustering based on the normalized mutual information between pre-learned pseudo-labels and quantified genes. Additionally, AIGS incorporates a scale-invariant distance metric to assess cell-to-cell similarity, enhancing connections between homogenous cells and ensuring more accurate and robust results. Through comprehensive comparisons with state-of-the-art techniques, AIGS demonstrates superior performance in both clustering accuracy and multi-resolution visualization quality. Our in-depth analysis of clustering and visualization results further reveals that AIGS can uncover complex, stage-specific gene expression patterns during the same developmental cell stage.

bioinformatics↗

bioRxiv2024

Evaluation of Machine Learning Models for Aqueous Solubility Prediction in Drug Discovery

Determining the aqueous solubility of the chemical compound is of great importance in-silico drug discovery. However, correctly and rapidly predicting the aqueous solubility remains a challenging task. This paper explores and evaluates the predictability of multiple machine learning models in the aqueous solubility of compounds. Specifically, we apply a series of machine learning algorithms, including Random Forest, XG-Boost, LightGBM, and CatBoost, on a well-established aqueous solubility dataset (i. e., the Huuskonen dataset) of over 1200 compounds. Experimental results show that even traditional machine learning algorithms can achieve satisfactory performance with high accuracy. In addition, our investigation goes beyond mere prediction accuracy, delving into the interpretability of models to identify key features and understand the molecular properties that influence the predicted outcomes. This study sheds light on the ability to use machine learning approaches to predict compound solubility, significantly shortening the time that researchers spend on new drug discovery.

molecular biology↗

bioRxiv2022

Engineering precise adenine base editor with infinitesimal rates of bystander mutations and off-target editing

Adenine base editors (ABEs) catalyze A-to-G transitions showing broad applications, but their bystander mutations and off-target editing effects raise the concerns of safety issues. Through structure-guided engineering, we found ABE8e with an N108Q mutation reduced both adenine and cytosine bystander editing, and introduction of an additional L145T mutation (ABE9), further refined the editing window to 1-2nt with eliminated cytosine editing. Importantly, ABE9 induced very minimal RNA and undetectable Cas9-independent DNA off-target effects, which mainly installed desired single A-to-G conversion in mouse and rat embryos to efficiently generate disease models. Moreover, ABE9 accurately edited A5 position of the protospacer sequence in pathogenic homopolymeric adenosine sites (up to 342.5-fold precision than ABE8e) and was further confirmed through a library of guide RNA-target sequence pairs. Due to the minimized editing window, ABE9 could further broaden the targeting scope for precise correction of pathogenic SNVs when fused to Cas9 variants with expanded PAM compatibility.

bioengineering↗

bioRxiv2019

Calcium induced calcium release in proximity to hair cell BK channels revealed by PKA activation

Large conductance calcium-activated potassium (BK) channels play a critical role in electrical resonance, a mechanism of frequency selectivity in chicken hair cells. We determine that BK currents are dependent on inward flow of Ca2+, and intracellular buffering of Ca2+. Entry of Ca2+ is further amplified locally by Ca2+ induced Ca2+ release (CICR) in close proximity to plasma membrane BK channels. Ca2+ imaging reveals peripheral clusters of high concentrations of Ca2+ that are suprathreshold to that needed to activate BK channels. PKA activation increases BK currents likely by recruiting more BK channels due to spatial spread of high Ca2+ concentrations in turn from increasing CICR. STORM imaging confirms the presence of nanodomains with ryanodine and IP3 receptors in close proximity to the Slo subunit of BK channels. Together, these data require a rethinking of how electrical resonance is brought about and suggest effects of CICR in synaptic release. Both genders were included in this study.

physiology↗