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@article{fanelli2012negative,
title={Negative results are disappearing from most disciplines and countries},
author={Fanelli, Daniele},
journal={Scientometrics},
volume={90},
number={3},
pages={891--904},
year={2012},
publisher={Springer}
}
@article{mlinaric2017dealing,
title={Dealing with the positive publication bias: Why you should really publish your negative results},
author={Mlinaric, Ana and Horvat, Martina and Smolcic, Vesna Supak},
journal={Biochemia medica},
volume={27},
number={3},
pages={030201},
year={2017}
}
% ===== DTI Benchmarks & Databases =====
@article{gaulton2017chembl,
title={{ChEMBL}: a large-scale bioactivity database for drug discovery},
author={Gaulton, Anna and Hersey, Anne and Nowotka, Micha{\l} and Bento, A Patr{\'\i}cia and Chambers, Jon and Mendez, David and Mutowo, Prudence and Atkinson, Francis and Bellis, Louisa J and Cibri{\'a}n-Uhalte, Elena and others},
journal={Nucleic Acids Research},
volume={45},
number={D1},
pages={D986--D994},
year={2017},
publisher={Oxford University Press}
}
@article{kim2023pubchem,
title={{PubChem} 2023 update},
author={Kim, Sunghwan and Chen, Jie and Cheng, Tiejun and Gindulyte, Asta and He, Jia and He, Siqian and Li, Qingliang and Shoemaker, Benjamin A and Thiessen, Paul A and Yu, Bo and others},
journal={Nucleic Acids Research},
volume={51},
number={D1},
pages={D1373--D1380},
year={2023},
publisher={Oxford University Press}
}
@article{gilson2016bindingdb,
title={{BindingDB} in 2015: a public database for medicinal chemistry, computational chemistry and systems pharmacology},
author={Gilson, Michael K and Liu, Tiqing and Baitaluk, Michael and Nicola, George and Hwang, Linda and Chong, Jenny},
journal={Nucleic Acids Research},
volume={44},
number={D1},
pages={D1045--D1053},
year={2016},
publisher={Oxford University Press}
}
@article{davis2011comprehensive,
title={Comprehensive analysis of kinase inhibitor selectivity},
author={Davis, Mindy I and Hunt, Jeremy P and Herrgard, Sune and Ciceri, Pietro and Wodicka, Lisa M and Pallares, Gabriel and Hocker, Michael and Treiber, Daniel K and Zarrinkar, Patrick P},
journal={Nature Biotechnology},
volume={29},
number={11},
pages={1046--1051},
year={2011},
publisher={Nature Publishing Group}
}
@article{huang2021therapeutics,
title={Therapeutics Data Commons: Machine Learning Datasets and Tasks for Drug Discovery and Development},
author={Huang, Kexin and Fu, Tianfan and Gao, Wenhao and Zhao, Yue and Roohani, Yusuf and Leskovec, Jure and Coley, Connor W and Xiao, Cao and Sun, Jimeng and Zitnik, Marinka},
journal={Proceedings of NeurIPS Datasets and Benchmarks},
year={2021}
}
@article{mysinger2012dude,
title={Directory of useful decoys, enhanced ({DUD-E}): better ligands and decoys for better benchmarking},
author={Mysinger, Michael M and Carchia, Michael and Irwin, John J and Shoichet, Brian K},
journal={Journal of Medicinal Chemistry},
volume={55},
number={14},
pages={6582--6594},
year={2012},
publisher={ACS Publications}
}
@article{wu2018moleculenet,
title={{MoleculeNet}: a benchmark for molecular machine learning},
author={Wu, Zhenqin and Ramsundar, Bharath and Feinberg, Evan N and Gomes, Joseph and Geniesse, Caleb and Pappu, Aneesh S and Leswing, Karl and Pande, Vijay},
journal={Chemical Science},
volume={9},
number={2},
pages={513--530},
year={2018},
publisher={Royal Society of Chemistry}
}
@article{tran2020litpcba,
title={Lit-{PCBA}: An unbiased data set for machine learning and virtual screening},
author={Tran-Nguyen, Viet-Khoa and Jacquemard, Christophe and Rognan, Didier},
journal={Journal of Chemical Information and Modeling},
volume={60},
number={9},
pages={4263--4273},
year={2020},
publisher={ACS Publications}
}
@article{li2025evidti,
title={Negative is positive: on the role of negative evidence in drug-target interaction prediction},
author={Li, Jianmin and others},
journal={Briefings in Bioinformatics},
year={2025},
note={To appear}
}
@inproceedings{volkov2025welqrate,
title={{WelQrate}: Defining the gold standard in small molecule drug discovery benchmarking},
author={Volkov, Maxim and Fl{\"o}ge, Joseph and Stolte, Markus and others},
booktitle={Advances in Neural Information Processing Systems},
year={2025}
}
% ===== DTI Models =====
@article{ozturk2018deepdta,
title={{DeepDTA}: deep drug--target binding affinity prediction},
author={{\"O}zt{\"u}rk, Hakime and {\"O}zg{\"u}r, Arzucan and Ozkirimli, Elif},
journal={Bioinformatics},
volume={34},
number={17},
pages={i821--i829},
year={2018},
publisher={Oxford University Press}
}
@article{nguyen2021graphdta,
title={{GraphDTA}: predicting drug--target binding affinity with graph neural networks},
author={Nguyen, Thin and Le, Hang and Quinn, Thomas P and Nguyen, Tri and Le, Thuc Duy and Venkatesh, Svetha},
journal={Bioinformatics},
volume={37},
number={8},
pages={1140--1147},
year={2021},
publisher={Oxford University Press}
}
@article{bai2023drugban,
title={Interpretable bilinear attention network with domain adaptation improves drug--target prediction},
author={Bai, Peizhen and Miljkovi{\'c}, Filip and John, Bino and Lu, Haiping},
journal={Nature Machine Intelligence},
volume={5},
number={2},
pages={126--136},
year={2023},
publisher={Nature Publishing Group}
}
% ===== Clinical Trial Databases =====
@article{tasneem2012aact,
title={The database for aggregate analysis of {ClinicalTrials.gov} ({AACT}) and subsequent regrouping by clinical specialty},
author={Tasneem, Asba and Aberle, Laura and Ananber, Hari and Chakraborty, Swati and Chiswell, Karen and McCourt, Brian J and Pietrobon, Ricardo},
journal={PLoS ONE},
volume={7},
number={3},
pages={e33677},
year={2012}
}
@article{fu2022hint,
title={{HINT}: Hierarchical interaction network for clinical trial outcome prediction},
author={Fu, Tianfan and Huang, Kexin and Xiao, Cao and Glass, Lucas M and Sun, Jimeng},
journal={Patterns},
volume={3},
number={4},
pages={100445},
year={2022},
publisher={Elsevier}
}
@article{siah2021cto,
title={Predicting drug approvals: the {Novartis} data science and artificial intelligence challenge},
author={Siah, Kien Wei and Kelley, Nicholas W and Engstrom, Steinar and Abi Jaoude, Joseph and Cook, Andrew R and Lo, Andrew W},
journal={Patterns},
volume={2},
number={8},
pages={100312},
year={2021},
publisher={Elsevier}
}
@article{shi2024safety,
title={Safety and efficacy outcomes in clinical trials with negative results},
author={Shi, Yu and Du, Jingcheng},
journal={Drug Safety},
year={2024},
publisher={Springer}
}
@misc{opentargets2024,
title={Open Targets Platform},
author={{Open Targets Consortium}},
year={2024},
howpublished={\url{https://platform.opentargets.org/}}
}
% ===== PPI Databases =====
@article{luck2020huri,
title={A reference map of the human binary protein interactome},
author={Luck, Katja and Kim, Dae-Kyum and Lambourne, Luke and Spirohn, Kerstin and Begg, Bridget E and Bian, Wenting and Brber, Ruth and Bridges, Nora and Cho, Sohyun and others},
journal={Nature},
volume={580},
number={7803},
pages={402--408},
year={2020},
publisher={Nature Publishing Group}
}
@article{orchard2014intact,
title={The {MIntAct} project---{IntAct} as a common curation platform for 11 molecular interaction databases},
author={Orchard, Sandra and Ammari, Mais and Aranda, Bruno and Breuza, Lionel and Briganti, Leonardo and Broackes-Carter, Fiona and others},
journal={Nucleic Acids Research},
volume={42},
number={D1},
pages={D358--D363},
year={2014},
publisher={Oxford University Press}
}
@article{drew2021humap,
title={hu.{MAP} 2.0: integration of over 15,000 proteomic experiments builds a global compendium of human multiprotein assemblies},
author={Drew, Kevin and Wallingford, John B and Marcotte, Edward M},
journal={Molecular Systems Biology},
volume={17},
number={5},
pages={e10016},
year={2021},
publisher={EMBO Press}
}
@article{szklarczyk2023string,
title={{STRING} v12.0: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets},
author={Szklarczyk, Damian and Kirsch, Rebecca and Koutrouli, Mikaela and Nastou, Katerina and Mehryary, Farrokh and Hachilif, Radja and Gable, Annika L and Fang, Tao and Doncheva, Nadezhda T and Pyysalo, Sampo and others},
journal={Nucleic Acids Research},
volume={51},
number={D1},
pages={D483--D489},
year={2023},
publisher={Oxford University Press}
}
@article{uniprot2023,
title={The {UniProt} Consortium. {UniProt}: the Universal Protein Knowledgebase in 2023},
author={{UniProt Consortium}},
journal={Nucleic Acids Research},
volume={51},
number={D1},
pages={D523--D531},
year={2023}
}
% ===== LLM Benchmarks =====
@article{mirza2024chembench,
title={{ChemBench}: A large-scale benchmark for chemical reasoning in language models},
author={Mirza, Adrian and others},
journal={Advances in Neural Information Processing Systems},
year={2024}
}
@article{fang2024molinstructions,
title={Mol-Instructions: A large-scale biomolecular instruction dataset for large language models},
author={Fang, Yin and Liang, Xiaozhuo and Zhang, Ningyu and Liu, Kangwei and Huang, Rui and Chen, Zhuo and Fan, Xiaohui and Chen, Huajun},
journal={Proceedings of ICLR},
year={2024}
}
@article{jin2021medqa,
title={What disease does this patient have? {A} large-scale open domain question answering dataset from medical exams},
author={Jin, Di and Pan, Eileen and Oufattole, Nassim and Weng, Wei-Hung and Fang, Hanyi and Szolovits, Peter},
journal={Applied Sciences},
volume={11},
number={14},
pages={6421},
year={2021}
}
@article{laurent2024labbench,
title={{LAB-Bench}: Measuring capabilities of language models for biology research},
author={Laurent, Jon M and Gershon, Jo{\~a}o and others},
journal={arXiv preprint arXiv:2407.10362},
year={2024}
}
% ===== LLM Models =====
@article{dubey2024llama3,
title={The {Llama} 3 herd of models},
author={Dubey, Abhimanyu and others},
journal={arXiv preprint arXiv:2407.21783},
year={2024}
}
@article{yang2024qwen2,
title={{Qwen2} technical report},
author={Yang, An and others},
journal={arXiv preprint arXiv:2407.10671},
year={2024}
}
@misc{openai2024gpt4o,
title={{GPT-4o} system card},
author={{OpenAI}},
year={2024},
howpublished={\url{https://openai.com/index/gpt-4o-system-card/}}
}
@misc{google2025gemini,
title={{Gemini} 2.5 Flash},
author={{Google DeepMind}},
year={2025},
howpublished={\url{https://deepmind.google/technologies/gemini/}}
}
@misc{anthropic2025claude,
title={Claude {Haiku} 4.5 Model Card},
author={{Anthropic}},
year={2025},
howpublished={\url{https://www.anthropic.com}}
}
% ===== Methodology =====
@article{gebru2021datasheets,
title={Datasheets for Datasets},
author={Gebru, Timnit and Morgenstern, Jamie and Vecchione, Briana and Vaughan, Jennifer Wortman and Wallach, Hanna and III, Hal Daum{\'e} and Crawford, Kate},
journal={Communications of the ACM},
volume={64},
number={12},
pages={86--92},
year={2021}
}
@inproceedings{akhtar2024croissant,
title={Croissant: A Metadata Format for {ML}-Ready Datasets},
author={Akhtar, Mubashara and Benjelloun, Omar and Conforti, Costanza and van der Maaten, Laurens and others},
booktitle={Proceedings of KDD},
year={2024}
}
@inproceedings{chen2016xgboost,
title={{XGBoost}: A scalable tree boosting system},
author={Chen, Tianqi and Guestrin, Carlos},
booktitle={Proceedings of KDD},
pages={785--794},
year={2016}
}
@article{karypis1998metis,
title={A fast and high quality multilevel scheme for partitioning irregular graphs},
author={Karypis, George and Kumar, Vipin},
journal={SIAM Journal on Scientific Computing},
volume={20},
number={1},
pages={359--392},
year={1998}
}
% ===== Contamination & Evaluation =====
@article{sainz2024contamination,
title={Data contamination report from the 2024 {NAACL} workshop},
author={Sainz, Oscar and others},
journal={arXiv preprint},
year={2024}
}
@article{balloccu2024leak,
title={Leak, cheat, repeat: Data contamination and evaluation malpractices in closed-source {LLMs}},
author={Balloccu, Simone and others},
journal={Proceedings of EACL},
year={2024}
}
% ===== Splitting Strategies =====
@article{yang2019cold,
title={Analyzing learned molecular representations for property prediction},
author={Yang, Kevin and Swanson, Kyle and Jin, Wengong and Coley, Connor and Eiden, Philipp and Gao, Hua and Guzman-Perez, Angel and Hopper, Timothy and Kelley, Brian and Mathea, Miriam and others},
journal={Journal of Chemical Information and Modeling},
volume={59},
number={8},
pages={3370--3388},
year={2019},
publisher={ACS Publications}
}
@article{bemis1996murcko,
title={The properties of known drugs. 1. Molecular frameworks},
author={Bemis, Guy W and Murcko, Mark A},
journal={Journal of Medicinal Chemistry},
volume={39},
number={15},
pages={2887--2893},
year={1996}
}
% ===== PPI Models =====
@article{chen2019pipr,
title={Multifaceted protein--protein interaction prediction based on {Siamese} residual {RCNN}},
author={Chen, Muhao and Ju, Chelsea J-T and Zhou, Guangyu and Chen, Xuelu and Zhang, Tianle and Chang, Kai-Wei and Zaniolo, Carlo and Wang, Wei},
journal={Bioinformatics},
volume={35},
number={14},
pages={i305--i314},
year={2019},
publisher={Oxford University Press}
}
@article{zheng2020ddb,
title={Predicting drug--target interactions using drug--drug and target--target similarities},
author={Zheng, Yi and Wu, Zheng},
journal={BMC Bioinformatics},
year={2020}
}
% ===== LogAUC & Metrics =====
@article{mysinger2010logauc,
title={Rapid context-dependent ligand desolvation in molecular docking},
author={Mysinger, Michael M and Shoichet, Brian K},
journal={Journal of Chemical Information and Modeling},
volume={50},
number={9},
pages={1561--1573},
year={2010}
}
@article{truchon2007bedroc,
title={Evaluating virtual screening methods: good and bad metrics for the ``early recognition'' problem},
author={Truchon, Jean-Fran{\c{c}}ois and Bayly, Christopher I},
journal={Journal of Chemical Information and Modeling},
volume={47},
number={2},
pages={488--508},
year={2007}
}
% ===== General ML =====
@article{matthews1975mcc,
title={Comparison of the predicted and observed secondary structure of {T4} phage lysozyme},
author={Matthews, Brian W},
journal={Biochimica et Biophysica Acta (BBA)-Protein Structure},
volume={405},
number={2},
pages={442--451},
year={1975}
}
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