% ===== Negative Results & Publication Bias =====

@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}
}