Mengji Zhang

I am a Postdoc Associate at Yale University as of June 2024. I received my PhD supervised by Prof. Kun Qian in Shanghai Jiao Tong University in June, 2023. My research focuses on computational biology. My long-term research goal is to advance the understanding of biological problems with computational algorithms.

I am collaborating with Prof. Hyojung Seo from Yale University on modeling the neural dynamics to explain the relationship between nerual activities and behavior.

If you are interested in collaboration with me about computational biology, please contact mengji.zhang0809@gmail.com.

Research interests

Computational omics Computational neuroscience

Software

DeepAdapter is available as a PyPi package. This tool can remove unwanted variations caused by batch effects, platform differences, purity, and other unknown factors in transcriptomic studies. You can find the source code on GitHub. Try it by running: pip install deepadapter.

Highlighted Research

Integrating the large-scale and heterogenous transcriptome datasets. Learn more

Research Project 1

Accurate identification of true biological signals from diverse undesirable variations in large-scale transcriptomes is essential for downstream discoveries. Herein, we develop a universal deep neural network, called DeepAdapter, to eliminate various undesirable variations from transcriptomic data. The innovation of our approach lies in automatic learning of the corresponding denoising strategies to adapt to different situations.

Decoding the relationship between olfactory perception and molecular structure. Learn more

Research Project 2

While visual and auditory information conveyed by wavelength of light and frequency of sound have been decoded, predicting olfactory information remains challenging due to the unknown and potentially discontinuous perceptual space of smells and odorants. Herein, we develop a deep learning model called Mol-PECO (Molecular Representation by Positional Encoding of Coulomb Matrix) to predict olfactory perception from molecular structures.

Stabilizing the metabolic profilings. Learn more

Research Project 3

Although mass spectrometry (MS) of metabolites has the potential to provide real-time monitoring of patient status for diagnostic purposes, the diagnostic application of MS is limited due to sample treatment and data quality/reproducibility. Here, the generation of a deep stabilizer for ultra-fast, label-free MS detection and the application of this method for serum metabolic diagnosis of coronary heart disease (CHD) are reported.

Publications

Google Scholar Profile

2024
  1. Mengji Zhang et al. A self-adaptive and versatile tool for eliminating multiple undesirable variations from transcriptome. In submission, 2024 (First author, preprint in bioRxiv). Read more
  2. Mengji Zhang* et al. A deep position-encoding model for predicting olfactory perception from molecular structures and electrostatics. npj Systems Biology and Applications, 2024, 10, 76 (First author, IF 4.3). Read more
  3. Haiyang Su … Mengji Zhang et al. Fast Label‐Free Metabolic Profile Recognition Identifies Phenylketonuria and Subtypes. Advanced Science 2024, 2305701. Read more
2023
  1. Weikang Shu#, Mengji Zhang# et al. An Alloy Platform of Dual-Fingerprints for High-Performance Stroke Screening. Advanced Functional Materials 2023, 2210267. (Co-first author, IF 18.81). Read more
  2. Jing Cao#, Yan Xiao#, Mengji Zhang# et al. Deep learning of dual plasma fingerprints for high-performance infection classification. Small 2023, 202206349. (Co-first author, IF 15.15). Read more
  3. Shunxiang Li … Mengji Zhang et al. Serum Metabolic Fingerprints Characterize Systemic Lupus Erythematosus. Advanced Science 2023, 2304610. Read more
2022
  1. Lin Wang#, Mengji Zhang#, Xufeng Pan#, Mingna Zhao# et al. Integrative Serum Metabolic Fingerprints Based Multi-Modal Platforms for Lung Adenocarcinoma Early Detection and Pulmonary Nodule Classification. Advanced Science 2022, 2203786. (Co-first author, IF 16.80). Read more
  2. Xia Yin#, Jing Yang#, Mengji Zhang#, Xinyao Wang# et al. Serum Metabolic Fingerprints on Bowl-Shaped Submicroreactor Chip for Chemotherapy Monitoring. ACS Nano 2022. (Co-first author, IF 15.88). Read more
  3. Mengji Zhang# et al. Plasma metabolic signature of cardiovascular and cerebrovascular diseases from a large cohort study. Journal of Shanghai Jiao Tong University (Medical Science) 2022, 2, 259. Read more
2021
  1. Mengji Zhang et al. Ultra-Fast Label-Free Serum Metabolic Diagnosis of Coronary Heart Disease via a Deep Stabilizer. Advanced Science 2021, 8, 2101333. (First author, IF 16.80). Read more
  2. Haiyang Su … Mengji Zhang et al. Plasmonic alloys reveal distinct metabolic phenotype of early gastric cancer. Advanced Materials 2021, 33, 2007978. Read more
2020
  1. Jing Yang … Mengji Zhang et al. Urine Metabolic Fingerprints Encode Subtypes of Kidney Diseases. Angewandte Chemie-International Edition, 2020, 59, 1703. Read more
  2. Jing Cao … Mengji Zhang et al. Metabolic fingerprinting on synthetic alloys for medulloblastoma diagnosis and radio therapy evaluation. Advanced Materials 2020, 32, 2000906. Read more
2019
  1. Mengji Zhang et al. Predicting Stock Trends Based on News Events. Data Analysis and Knowledge Discovery, 2019, 3, 11. (First author). Read more
  2. Xinyu Wang … Mengji Zhang et al. An Effective Optimization Algorithm for Application Mapping in Network-on-Chip Designs. IEEE Transactions on Industrial Electronics, 2019, 67, 5798. (IF 8.14). Read more