1 code implementation • 14 Feb 2024 • Botao Yu, Frazier N. Baker, Ziqi Chen, Xia Ning, Huan Sun
Using SMolInstruct, we fine-tune a set of open-source LLMs, among which, we find that Mistral serves as the best base model for chemistry tasks.
no code implementations • 13 Feb 2024 • Bo Peng, Xinyi Ling, Ziru Chen, Huan Sun, Xia Ning
Both the ECInstruct dataset and the eCeLLM models show great potential in empowering versatile and effective LLMs for e-commerce.
1 code implementation • 29 Jan 2024 • Vishal Dey, Xia Ning
Pretrained Graph Neural Networks have been widely adopted for various molecular property prediction tasks.
no code implementations • 13 Nov 2023 • Bo Peng, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning
As widely demonstrated in the literature, this issue could lead to a loss of information in individual items, and significantly degrade models' scalability and performance.
no code implementations • 23 Oct 2023 • Shunian Xiang, Patrick J. Lawrence, Bo Peng, ChienWei Chiang, Dokyoon Kim, Li Shen, Xia Ning
Thus, leveraging learned embeddings allows MPI to effectively differentiate the importance among paths.
no code implementations • 20 Oct 2023 • Patrick J. Lawrence, Xia Ning
In this work, we propose the use of contrastive learning to improve learned drug and cell line representations by preserving relationship structures associated with drug mechanism of action and cell line cancer types.
no code implementations • 2 Oct 2023 • Bo Peng, Ben Burns, Ziqi Chen, Srinivasan Parthasarathy, Xia Ning
In addition, SSNA adapts the top-a layers of LLMs jointly, and integrates adapters sequentially for enhanced effectiveness (i. e., recommendation performance).
no code implementations • 18 Sep 2023 • Bo Peng, Srinivasan Parthasarathy, Xia Ning
Our experimental results demonstrate that ANT does not suffer from the negative transfer issue on any of the target tasks.
1 code implementation • 6 Sep 2023 • Frazier N. Baker, Ziqi Chen, Daniel Adu-Ampratwum, Xia Ning
Retrosynthesis is the process of determining the set of reactant molecules that can react to form a desired product.
no code implementations • 23 Aug 2023 • Ziqi Chen, Bo Peng, Srinivasan Parthasarathy, Xia Ning
Ligand-based drug design aims to identify novel drug candidates of similar shapes with known active molecules.
1 code implementation • 30 Jun 2023 • Vishal Dey, Xia Ning
To address this, we developed neural ranking approaches that leverage large-scale drug response data across multiple cell lines from diverse cancer types.
no code implementations • 2 Mar 2023 • Ziqi Chen, Martin Renqiang Min, Hongyu Guo, Chao Cheng, Trevor Clancy, Xia Ning
This process is known as TCR recognition and constitutes a key step for immune response.
no code implementations • 16 Sep 2022 • Bo Peng, Srinivasan Parthasarathy, Xia Ning
Our run-time performance comparison signifies that RAM could also be more efficient on benchmark datasets.
1 code implementation • 10 Jun 2022 • Ziqi Chen, Oluwatosin R. Ayinde, James R. Fuchs, Huan Sun, Xia Ning
It first predicts the reaction centers in the target molecules (products), identifies the synthons needed to assemble the products, and transforms these synthons into reactants.
no code implementations • 4 Jun 2022 • Bo Peng, Chang-Yu Tai, Srinivasan Parthasarathy, Xia Ning
In this manuscript, we develop prospective preference enhanced mixed attentive model (P2MAM) to generate session-based recommendations using two important factors: temporal patterns and estimates of users' prospective preferences.
1 code implementation • 14 Nov 2021 • Vishal Dey, Raghu Machiraju, Xia Ning
In order to cope with limited training data for a target task, transfer learning for SAR modeling has been recently adopted to leverage information from data of related tasks.
no code implementations • 9 Sep 2021 • Athanasios N. Nikolakopoulos, Xia Ning, Christian Desrosiers, George Karypis
Collaborative recommendation approaches based on nearest-neighbors are still highly popular today due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations.
2 code implementations • 8 Dec 2020 • Ziqi Chen, Martin Renqiang Min, Srinivasan Parthasarathy, Xia Ning
A pipeline of multiple, identical Modof models is implemented into Modof-pipe to modify an input molecule at multiple disconnection sites.
1 code implementation • 4 Dec 2020 • Ziqi Chen, Martin Renqiang Min, Xia Ning
T-cell receptors can recognize foreign peptides bound to major histocompatibility complex (MHC) class-I proteins, and thus trigger the adaptive immune response.
no code implementations • 25 Aug 2020 • Vishal Dey, Peter Krasniak, Minh Nguyen, Clara Lee, Xia Ning
Our study provides the first analysis and derived knowledge of BII from social media using NLP techniques, and demonstrates the potential of using social media information to better understand similar emerging illnesses.
no code implementations • 12 Aug 2020 • Yonghyun Nam, Jae-Seung Yun, Seung Mi Lee, Ji Won Park, Ziqi Chen, Brian Lee, Anurag Verma, Xia Ning, Li Shen, Dokyoon Kim
To reduce trial and error in finding treatments for COVID-19, we propose building a network-based drug repurposing framework to prioritize repurposable drugs.
no code implementations • 12 Aug 2020 • Ziwei Fan, Evan Burgun, Zhiyun Ren, Titus Schleyer, Xia Ning
This method recommends relevant information from electronic health records for physicians during patient visits.
no code implementations • 19 Jul 2020 • Zhiyun Ren, Bo Peng, Titus K. Schleyer, Xia Ning
With increasing and extensive use of electronic health records, clinicians are often under time pressure when they need to retrieve important information efficiently among large amounts of patients' health records in clinics.
3 code implementations • 3 Apr 2020 • Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
We compared M2 with different combinations of the factors with 5 state-of-the-art next-basket recommendation methods on 4 public benchmark datasets in recommending the first, second and third next basket.
2 code implementations • 27 Feb 2020 • Bo Peng, Zhiyun Ren, Srinivasan Parthasarathy, Xia Ning
We compared HAM models with the most recent, state-of-the-art methods on six public benchmark datasets in three different experimental settings.
no code implementations • 18 Feb 2020 • Bo Peng, Xiaohui Yao, Shannon L. Risacher, Andrew J. Saykin, Li Shen, Xia Ning
This method learns the latent scoring function that pushes the most effective cognitive assessments onto the top of the prioritization list.
no code implementations • 15 Nov 2019 • Bo Peng, Renqiang Min, Xia Ning
We also present an extension of this model, which incorporates descriptions of entities and learns a second set of entity embeddings from the descriptions.
no code implementations • 22 Feb 2019 • Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning
Background: The problem of predicting whether a drug combination of arbitrary orders is likely to induce adverse drug reactions is considered in this manuscript.
no code implementations • 8 Mar 2018 • Wen-Hao Chiang, Li Shen, Lang Li, Xia Ning
Adverse drug reactions (ADRs) induced from high-order drug-drug interactions (DDIs) due to polypharmacy represent a significant public health problem.
no code implementations • 23 Jan 2018 • Yicheng He, Junfeng Liu, Xia Ning
We have developed a new learning-to-rank method, denoted as pLETORg , that predicts drug ranking structures in each cell line via using drug latent vectors and cell line latent vectors.
no code implementations • 17 Jan 2018 • Zhiyun Ren, Xia Ning, Huzefa Rangwala
Grade prediction methods seek to estimate a grade that a student may achieve in a course that she may take in the future (e. g., next term).
no code implementations • 15 Sep 2017 • Zhiyun Ren, Xia Ning, Huzefa Rangwala
The grade of a student on a course is modeled as the similarity of their latent representation in the "knowledge" space.
no code implementations • 14 Jan 2016 • Baichuan Zhang, Sutanay Choudhury, Mohammad Al Hasan, Xia Ning, Khushbu Agarwal, Sumit Purohit, Paola Pesntez Cabrera
Link prediction, or predicting the likelihood of a link in a knowledge graph based on its existing state is a key research task.