MedScan, a natural language processing engine for MEDLINE abstracts

Natural Language Understanding

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A General Natural-language Text Processor for Clinical Radiology

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Lexical-Functional Grammar: A Formal System for Grammatical Representation

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GENIES: a natural-language processing system for the extraction of molecular pathways from journal articles

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Automatic extraction of biological information from scientific text: protein-protein interactions.

Blaschke, C., Andrade-Navarro, M. A., Ouzounis, C. A., & Valencia, A. (1999) · PubMed · Cited by 448 · see citing works

Automated extraction of information on protein–protein interactions from the biological literature

Ono, T., Hishigaki, H., Tanigami, A., & Takagi, T. (2001) · Bioinformatics · doi:10.1093/bioinformatics/17.2.155 · Cited by 398 · see citing works

Lectures on contemporary syntactic theories

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Automatic Extraction of Protein Interactions from Scientific Abstracts

Thomas, J., Milward, D., Ouzounis, C. A., Pulman, S., & Carroll, M. (1999) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447331_0051 · Cited by 250 · see citing works

EVENT EXTRACTION FROM BIOMEDICAL PAPERS USING A FULL PARSER

Yakushiji, A., Tateisi, Y., Miyao, Y., & Tsujii, J. (2000) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447362_0040 · Cited by 226 · see citing works

Identifying the Interaction between Genes and Gene Products Based on Frequently Seen Verbs in Medline Abstracts.

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Two Applications of Information Extraction to Biological Science Journal Articles: Enzyme Interactions and Protein Structures

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BIDIRECTIONAL INCREMENTAL PARSING FOR AUTOMATIC PATHWAY IDENTIFICATION WITH COMBINATORY CATEGORIAL GRAMMAR

Park, J. C., Kim, H. S., & Kim, J. (2000) · Pacific Symposium on Biocomputing (PSB) · doi:10.1142/9789814447362_0039 · Cited by 142 · see citing works

Toward Routine Automatic Pathway Discovery from On-line Scientific Text Abstracts.

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SRI International FASTUS system

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Natural Language Understanding

Sarang, P. (2020) · Apress eBooks · doi:10.1007/978-1-4842-6150-7_9 · Cited by 125 · see citing works

SRI International FASTUS System MUC-6 Test Results and Analysis

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Extending a natural language parser with UMLS knowledge.

McCray, A. T. (1991) · PubMed · Cited by 28 · see citing works

A survey of current work in biomedical text mining

Cohen, A. M. (2005) · Briefings in Bioinformatics · doi:10.1093/bib/6.1.57 · Cited by 767 · see citing works

Corpus annotation for mining biomedical events from literature

Kim, J.-D., Ohta, T., & Tsujii, J. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-10 · Cited by 395 · see citing works

Content-rich biological network constructed by mining PubMed abstracts

Chen, H., & Sharp, B. M. (2004) · BMC Bioinformatics · doi:10.1186/1471-2105-5-147 · Cited by 345 · see citing works

Smart health: Big data enabled health paradigm within smart cities

Pramanik, M. I., Lau, R. Y. K., Demirkan, H., & Azad, M. A. K. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.06.027 · Cited by 341 · see citing works

Modulation of anti-apoptotic and survival pathways by curcumin as a strategy to induce apoptosis in cancer cells

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Text mining and ontologies in biomedicine: Making sense of raw text

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Biomedical text mining and its applications in cancer research

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Extracting human protein interactions from MEDLINE using a full-sentence parser

Daraselia, N., Yuryev, A., Egorov, S., Novichkova, S., Nikitin, A., & Mazo, I. A. (2004) · Bioinformatics · doi:10.1093/bioinformatics/btg452 · Cited by 237 · see citing works

Duplication-divergence model of protein interaction network

Ispolatov, Y., Krapivsky, P. L., & Yuryev, A. (2005) · Physical Review E · doi:10.1103/physreve.71.061911 · Cited by 180 · see citing works

Binding properties and evolution of homodimers in protein-protein interaction networks

Ispolatov, I. (2005) · Nucleic Acids Research · doi:10.1093/nar/gki678 · Cited by 169 · see citing works

Chemopreventive potential of curcumin in prostate cancer

Teiten, M.-H., Gaascht, F., Eifes, S., Dicato, M. A., & Diederich, M. F. (2009) · Genes & Nutrition · doi:10.1007/s12263-009-0152-3 · Cited by 157 · see citing works

Developing specific molecular biomarkers for thermal stress in salmonids

Akbarzadeh, A., Günther, O. P., Houde, A. L. S., Li, S., Ming, T. J., Jeffries, K. M., Hinch, S. G., & Miller, K. M. (2018) · BMC Genomics · doi:10.1186/s12864-018-5108-9 · Cited by 152 · see citing works

Using the zebrafish model for Alzheimer’s disease research

Newman, M., Ebrahimie, E., & Lardelli, M. T. (2014) · Frontiers in Genetics · doi:10.3389/fgene.2014.00189 · Cited by 148 · see citing works

PASBio: predicate-argument structures for event extraction in molecular biology

Wattarujeekrit, T., Shah, P. K., & Collier, N. (2004) · BMC Bioinformatics · doi:10.1186/1471-2105-5-155 · Cited by 117 · see citing works

The next generation of literature analysis: Integration of genomic analysis into text mining

Scherf, M., Epple, A., & Werner, T. A. (2005) · Briefings in Bioinformatics · doi:10.1093/bib/6.3.287 · Cited by 101 · see citing works

Automatic pathway building in biological association networks

Yuryev, A., Mulyukov, Z., Kotelnikova, E. A., Maslov, S., Egorov, S., Nikitin, A., Daraselia, N., & Mazo, I. A. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-171 · Cited by 97 · see citing works

Protein–protein interaction predictions using text mining methods

Papanikolaou, N., Pavlopoulos, G. A., Θεοδοσίου, Θ., & Iliopoulos, I. (2014) · Methods · doi:10.1016/j.ymeth.2014.10.026 · Cited by 91 · see citing works

MOLECULAR NETWORKS IN MICROARRAY ANALYSIS

Sivachenko, A., Yuryev, A., Daraselia, N., & Mazo, I. A. (2007) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720007002795 · Cited by 89 · see citing works

A Machine Learning Approach for Identifying Disease-Treatment Relations in Short Texts

Frunza, O., Inkpen, D. Z., & Tran, T. T. D. (2010) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2010.152 · Cited by 89 · see citing works

A text-mining system for knowledge discovery from biomedical documents

Uramoto, N., Matsuzawa, H., Nagano, T., Murakami, A., Takeuchi, H., & Takeda, K. (2004) · IBM Systems Journal · doi:10.1147/sj.433.0516 · Cited by 88 · see citing works

Extracting interactions between proteins from the literature

Zhou, D., & He, Y. (2008) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2007.11.008 · Cited by 87 · see citing works

Large-Scale Analysis of Network Bistability for Human Cancers

Shiraishi, T., Matsuyama, S., & Kitano, H. (2010) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000851 · Cited by 75 · see citing works

Healthcare informatics and analytics in big data

Pramanik, M. I., Lau, R. Y. K., Azad, M. A. K., Hossain, M. S., Chowdhury, K. H., & Karmaker, B. K. (2020) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.113388 · Cited by 73 · see citing works

Ariadne's ChemEffect and Pathway Studio knowledge base

Yuryev, A., Kotelnikova, E. A., & Daraselia, N. (2009) · Expert Opinion on Drug Discovery · doi:10.1517/17460440903413488 · Cited by 72 · see citing works

Mining of relations between proteins over biomedical scientific literature using a deep-linguistic approach

Rinaldi, F., Schneider, G., Kaljurand, K., Heß, M., Andronis, C., Konstandi, O. A., & Persidis, A. (2006) · Artificial Intelligence in Medicine · doi:10.1016/j.artmed.2006.08.005 · Cited by 72 · see citing works

HyBrow: a prototype system for computer-aided hypothesis evaluation

Racunas, S. A., Shah, N. H., Albert, I., & Fedoroff, N. V. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth905 · Cited by 70 · see citing works

Extracting gene pathway relations using a hybrid grammar: the Arizona Relation Parser

McDonald, D. M., Chen, H., Su, H., & Marshall, B. B. (2004) · Bioinformatics · doi:10.1093/bioinformatics/bth409 · Cited by 66 · see citing works

IGF2BP3-mediated translation in cell protrusions promotes cell invasiveness and metastasis of pancreatic cancer

Taniuchi, K., Furihata, M., Hanazaki, K., Saito, M., & Saibara, T. (2014) · Oncotarget · doi:10.18632/oncotarget.2257 · Cited by 65 · see citing works

Pathway Analysis Tools and Toxicogenomics Reference Databases for Risk Assessment

Ganter, B., Zidek, N., Hewitt, P., Müller, D., & Vladimirova, A. (2007) · Pharmacogenomics · doi:10.2217/14622416.9.1.35 · Cited by 65 · see citing works

Automated assembly of molecular mechanisms at scale from text mining and curated databases

Bachman, J. A., Gyori, B. M., & Sorger, P. K. (2023) · Molecular Systems Biology · doi:10.15252/msb.202211325 · Cited by 64 · see citing works

An environment for relation mining over richly annotated corpora: the case of GENIA

Rinaldi, F., Schneider, G., Kaljurand, K., Heß, M., & Romacker, M. (2006) · BMC Bioinformatics · doi:10.1186/1471-2105-7-s3-s3 · Cited by 63 · see citing works

A pathway analysis of poly(I:C)-induced global gene expression change in human peripheral blood mononuclear cells

Huang, C. C., Duffy, K. E., Mateo, L. R. S., Amegadzie, B. Y., Sarisky, R. T., & Mbow, M. (2006) · Physiological Genomics · doi:10.1152/physiolgenomics.00002.2006 · Cited by 62 · see citing works

Plant Omics Data Center: An Integrated Web Repository for Interspecies Gene Expression Networks with NLP-Based Curation

Ohyanagi, H., Takano, T., Terashima, S., Kobayashi, M., Kanno, M., Morimoto, K., Kajiya‐Kanegae, H., Sasaki, Y., Saito, M., Asano, S., et al. (2014) · Plant and Cell Physiology · doi:10.1093/pcp/pcu188 · Cited by 60 · see citing works

A text-mining system for extracting metabolic reactions from full-text articles

Czarnecki, J., Nobeli, I., Smith, A. M., & Shepherd, A. J. (2012) · BMC Bioinformatics · doi:10.1186/1471-2105-13-172 · Cited by 58 · see citing works

Enhancement of anticancer activity by silibinin and paclitaxel combination on the ovarian cancer

Pashaei-Asl, F., Pashaei‐Asl, R., Khodadadi, K., Akbarzadeh, A., Ebrahimie, E., & Pashaiasl, M. (2017) · Artificial Cells Nanomedicine and Biotechnology · doi:10.1080/21691401.2017.1374281 · Cited by 58 · see citing works

ANDVisio: A new tool for graphic visualization and analysis of literature mined associative gene networks in the ANDSystem

Сергеевич, Д. П., Ivanisenko, T., Kolchanov, N. A., & Иванисенко, В. А. (2012) · In Silico Biology · doi:10.3233/isb-2012-0449 · Cited by 54 · see citing works

Adaptive immune response in osteoclastic bone resorption induced by orally administered Aggregatibacter actinomycetemcomitans in a rat model of periodontal disease

Li, Y., Messina, C., Bendaoud, M., Fine, D. H., Schreiner, H. C., & Tsiagbe, V. K. (2010) · Molecular Oral Microbiology · doi:10.1111/j.2041-1014.2010.00576.x · Cited by 50 · see citing works

Extraction of biological interaction networks from scientific literature

Skusa, A., Ruegg, A., & Köhler, J. (2005) · Briefings in Bioinformatics · doi:10.1093/bib/6.3.263 · Cited by 50 · see citing works

A general strategy for cellular reprogramming: The importance of transcription factor cross-repression

Crespo, I., & del Sol, A. (2013) · Stem Cells · doi:10.1002/stem.1473 · Cited by 47 · see citing works

Kernel‐based learning for biomedical relation extraction

Li, J., Zhang, Z., Li, X., & Chen, H. (2008) · Journal of the American Society for Information Science and Technology · doi:10.1002/asi.20791 · Cited by 47 · see citing works

IntEx

Ahmed, S. T., Chidambaram, D., Davulcu, H., & Baral, C. R. (2005) · doi:10.3115/1641484.1641492 · Cited by 45 · see citing works

Identification of Candidate Genes related to Bovine Marbling using Protein-Protein Interaction Networks

Lim, D., Kim, N.-K., Park, H., Lee, S. H., Cho, Y.-M., Oh, S. J., Kim, T.-H., & Kim, H. (2011) · International Journal of Biological Sciences · doi:10.7150/ijbs.7.992 · Cited by 45 · see citing works

Automatic mining of the literature to generate new hypotheses for the possible link between periodontitis and atherosclerosis: lipopolysaccharide as a case study

Hettne, K. M., Weeber, M., Laine, M. L., Cate, H. T., Boyer, S. K., Kors, J. A., & Loos, B. G. (2007) · Journal Of Clinical Periodontology · doi:10.1111/j.1600-051x.2007.01152.x · Cited by 44 · see citing works

Characterization of cell-type specific profiles in tissues and isolated cells from squamous cell carcinomas of the lung

Hawthorn, L., Stein, L. C., Panzarella, J. A., Loewen, G., & Baumann, H. (2006) · Lung Cancer · doi:10.1016/j.lungcan.2006.04.015 · Cited by 43 · see citing works

Detecting cellular reprogramming determinants by differential stability analysis of gene regulatory networks

Crespo, I., Perumal, T. M., Jurkowski, W., & del Sol, A. (2013) · BMC Systems Biology · doi:10.1186/1752-0509-7-140 · Cited by 42 · see citing works

Gene regulatory network analysis supports inflammation as a key neurodegeneration process in prion disease

Crespo, I., Roomp, K., Jurkowski, W., Kitano, H., & del Sol, A. (2012) · BMC Systems Biology · doi:10.1186/1752-0509-6-132 · Cited by 41 · see citing works

An in silico analysis of microRNAs: Mining the miRNAome

Murray, B. S., Choe, S. E., Woods, M. W., RYAN, T. E., & Liu, W. (2010) · Molecular BioSystems · doi:10.1039/c003961f · Cited by 40 · see citing works

Large-scale directional relationship extraction and resolution

Giles, C. B., & Wren, J. D. (2008) · BMC Bioinformatics · doi:10.1186/1471-2105-9-s9-s11 · Cited by 41 · see citing works

Proteome-wide and matrisome-specific atlas of the human ovary computes fertility biomarker candidates and open the way for precision oncofertility

Ouni, E., Nedbal, V., Pian, M. D., Cao, H., Haas, K. T., Peaucelle, A., Kerk, O. V., Herinckx, G., Marbaix, É., Dolmans, M., et al. (2022) · Matrix Biology · doi:10.1016/j.matbio.2022.03.005 · Cited by 38 · see citing works

Functional Genomic Responses to Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) and CFTRΔ508 in the Lung

Xu, Y. J., Liu, C., Clark, J. C., & Whitsett, J. A. (2006) · Journal of Biological Chemistry · doi:10.1074/jbc.m512072200 · Cited by 37 · see citing works

Clustering Gene Expression Regulators: New Approach to Disease Subtyping

Pyatnitskiy, M. A., Mazo, I. A., Shkrob, M., Schwartz, E., & Kotelnikova, E. A. (2014) · PLoS ONE · doi:10.1371/journal.pone.0084955 · Cited by 36 · see citing works

A Transcription Regulatory Sequence in the 5′ Untranslated Region of SARS-CoV-2 Is Vital for Virus Replication with an Altered Evolutionary Pattern against Human Inhibitory MicroRNAs

Dehcheshmeh, M. M., Moghbeli, S. M., Rahimirad, S., Alanazi, I. O., Shehri, Z. S. A., & Ebrahimie, E. (2021) · Cells · doi:10.3390/cells10020319 · Cited by 39 · see citing works

Identification of the key regulating genes of diminished ovarian reserve (DOR) by network and gene ontology analysis

Pashaiasl, M., Ebrahimi, M., & Ebrahimie, E. (2016) · Molecular Biology Reports · doi:10.1007/s11033-016-4025-8 · Cited by 34 · see citing works

A systems approach to mapping transcriptional networks controlling surfactant homeostasis

Xu, Y. J., Zhang, M., Wang, Y., Kadambi, P., Davé, V., Lu, L. J., & Whitsett, J. A. (2010) · BMC Genomics · doi:10.1186/1471-2164-11-451 · Cited by 34 · see citing works

Isolation, Characterization, Cryopreservation of Human Amniotic Stem Cells and Differentiation to Osteogenic and Adipogenic Cells

Aziz, S. G., Pashaei-Asl, F., Fardiazar, Z., & Pashaiasl, M. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158281 · Cited by 33 · see citing works

A baseline feature set for learning rhetorical zones using full articles in the biomedical domain

Mullen, T., Mizuta, Y., & Collier, N. (2005) · ACM SIGKDD Explorations Newsletter · doi:10.1145/1089815.1089823 · Cited by 33 · see citing works

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea

Lim, D., Strucken, E. M., Choi, B., Chai, H., Cho, Y. M., Jang, G. W., Kim, T. H., Gondro, C., & Lee, S. H. (2016) · PLoS ONE · doi:10.1371/journal.pone.0151324 · Cited by 32 · see citing works

Predicting missing expression values in gene regulatory networks using a discrete logic modeling optimization guided by network stable states

Crespo, I., Krishna, A., Béchec, A. L., & del Sol, A. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks785 · Cited by 31 · see citing works

Biological Information Extraction and Co-occurrence Analysis

Pavlopoulos, G. A., Promponas, V. J., Ouzounis, C., & Iliopoulos, I. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-0709-0_5 · Cited by 30 · see citing works

Machine learning methods to model multicellular complexity and tissue specificity

Sealfon, R. S. G., Wong, A. K., & Troyanskaya, O. G. (2021) · Nature Reviews Materials · doi:10.1038/s41578-021-00339-3 · Cited by 30 · see citing works

Global DNA methylation and transcriptional analyses of human ESC-derived cardiomyocytes

Gu, Y., Liu, G., Plongthongkum, N., Benner, C. W., Yi, F., Qu, J. T., Suzuki, K., Yang, J., Zhang, W., Li, M., et al. (2014) · Protein & Cell · doi:10.1007/s13238-013-0016-x · Cited by 31 · see citing works

Pathway analysis software as a tool for drug target selection, prioritization and validation of drug mechanism

Sivachenko, A., & Yuryev, A. (2007) · Expert Opinion on Therapeutic Targets · doi:10.1517/14728222.11.3.411 · Cited by 29 · see citing works

New insights into the expression profile of MicroRNA-34c and P53 in infertile men spermatozoa and testicular tissue

Rahbar, S., Novin, M. G., Alizadeh, E., Shahnazi, V., Pashaei-Asl, F., Badr, Y. A. A., Farzadi, L., Ebrahimie, E., & Pashaiasl, M. (2017) · Cellular and Molecular Biology · doi:10.14715/cmb/2017.63.8.17 · Cited by 28 · see citing works

Applied information retrieval and multidisciplinary research: new mechanistic hypotheses in Complex Regional Pain Syndrome

Hettne, K. M., de Mos, M., de Bruijn, A. G. J., Weeber, M., Boyer, S. K., van Mulligen, E. M., Cases, M., Mestres, J., & van der Lei, J. (2007) · Journal of Biomedical Discovery and Collaboration · doi:10.1186/1747-5333-2-2 · Cited by 28 · see citing works

KHSRP-bound small nucleolar RNAs associate with promotion of cell invasiveness and metastasis of pancreatic cancer

Taniuchi, K., & Ogasawara, M. (2020) · Oncotarget · doi:10.18632/oncotarget.27413 · Cited by 27 · see citing works

BIOIE: RETARGETABLE INFORMATION EXTRACTION AND ONTOLOGICAL ANNOTATION OF BIOLOGICAL INTERACTIONS FROM THE LITERATURE

Kim, J., & Park, J. C. (2004) · Journal of Bioinformatics and Computational Biology · doi:10.1142/s0219720004000739 · Cited by 27 · see citing works

Cancer Stem Cell Signaling during Repopulation in Head and Neck Cancer

Wilson, G. D., Thibodeau, B. J., Fortier, L. E., Pruetz, B. L., Galoforo, S., Marples, B., Baschnagel, A. M., Åkervall, J. A., & Huang, J. (2016) · Stem Cells International · doi:10.1155/2016/1894782 · Cited by 25 · see citing works

Brain protein expression changes in WAG/Rij rats, a genetic rat model of absence epilepsy after peripheral lipopolysaccharide treatment

Györffy, B., Kovács, Z., Gulyássy, P., Simor, A., Völgyi, K., Orbán, G., Baracskay, P., Szabó, Z., Janáky, T., Dobolyi, Á., et al. (2013) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2013.09.001 · Cited by 25 · see citing works

Bio-ModelChecker: Using Bounded Constraint Satisfaction to Seamlessly Integrate Observed Behavior With Prior Knowledge of Biological Networks

Sedghamiz, H., Morris, M., Craddock, T. J. A., Whitley, D., & Broderick, G. (2019) · Frontiers in Bioengineering and Biotechnology · doi:10.3389/fbioe.2019.00048 · Cited by 25 · see citing works

Long-Term Calorie Restriction Alters Anxiety-like Behaviour and the Brain and Adrenal Gland Transcriptomes of the Ageing Male Rat

Govic, A., Nasser, H. M., Levay, E. A., Zelko, M. D., Ebrahimie, E., Dehcheshmeh, M. M., Kent, S., Penman, J., & Hazi, A. (2022) · Nutrients · doi:10.3390/nu14214670 · Cited by 24 · see citing works

Quantitative analysis of Streptococcus pneumoniae TIGR4 response to in vitro iron restriction by 2‐D LC ESI MS/MS

Nanduri, B., Shah, P., Ramkumar, M., Allen, E. B., Swiatlo, E., Burgess, S. C., & Lawrence, M. L. (2008) · PROTEOMICS · doi:10.1002/pmic.200701048 · Cited by 24 · see citing works

Advanced literature analysis in a Big Data world

Cheadle, C., Cao, H., Kalinin, A., & Hodgkinson, J. (2016) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.13270 · Cited by 23 · see citing works

Prediction of sgRNA Off-Target Activity in CRISPR/Cas9 Gene Editing Using Graph Convolution Network

Vinodkumar, P. K., Ozcinar, C., & Anbarjafari, G. (2021) · Entropy · doi:10.3390/e23050608 · Cited by 22 · see citing works

Discrete Logic Modelling Optimization to Contextualize Prior Knowledge Networks Using PRUNET

Sánchez-Archidona, A. R., Crespo, I., Fournier, A., & del Sol, A. (2015) · PLoS ONE · doi:10.1371/journal.pone.0127216 · Cited by 21 · see citing works

Feasibility of Feature-based Indexing, Clustering, and Search of Clinical Trials

Boland, M. R., Miotto, R., Gao, J., & Weng, C. (2013) · Methods of Information in Medicine · doi:10.3414/me12-01-0092 · Cited by 21 · see citing works

Extracting Protein-Protein Interactions from the Literature Using the Hidden Vector State Model

Zhou, D., He, Y., & Kwoh, C. K. (2006) · Lecture notes in computer science · doi:10.1007/11758525_97 · Cited by 21 · see citing works

BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language

Hoyt, C. T., Domingo‐Fernándéz, D., & Hofmann‐Apitius, M. (2018) · Database · doi:10.1093/database/bay126 · Cited by 22 · see citing works

Comprehensive Analysis of Alternative Splicing and Functionality in Neuronal Differentiation of P19 Cells

Suzuki, H., Osaki, K., Sano, K., Alam, A. K., Nakamura, Y., Ishigaki, Y., Kawahara, K., & Tsukahara, T. (2011) · PLoS ONE · doi:10.1371/journal.pone.0016880 · Cited by 19 · see citing works

FLUTE: Fast and reliable knowledge retrieval from biomedical literature

Holtzapple, E., Telmer, C. A., & Miškov-Živanov, N. (2020) · Database · doi:10.1093/database/baaa056 · Cited by 19 · see citing works

LSAT: learning about alternative transcripts in MEDLINE

Shah, P. K., & Peer Bork, B. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btk044 · Cited by 19 · see citing works

The Zebrafish Equivalent of Alzheimer’s Disease-Associated PRESENILIN Isoform PS2V Regulates Inflammatory and Other Responses to Hypoxic Stress

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Anti-proliferative transcriptional effects of medroxyprogesterone acetate in estrogen receptor positive breast cancer cells are predominantly mediated by the progesterone receptor

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