Abstract
Philosophical discussions of the biomedical sciences have attracted considerable interest over the past few decades, with much of the debate focusing on causation, complex systems, and explanatory levels, each understood in different ways. Although a wide range of views has emerged, a small number of notions have played a prominent and cross-cutting role in understanding how biological systems function. These notions, i.e., mechanism, pathway, and network, are especially central in molecular biology, the field we focus on in this contribution. More specifically, we aim to provide a comprehensive analysis of the relations among these notions as they are employed in molecular biology, shedding light on the relationship between description and explanation, which we treat as two distinct epistemic activities.
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Notes
We assume, at least for our focus limited to molecular biology, that “pathway” and “process” can be taken as synonyms in that context. From now on, we will use only the first term even. The term used by the quoted author is kept in quotations.
Our interest is here devoted to epistemological issues. For some reflections on the relations between, e.g., a mechanistic ontology and pathways which refer to both neo-mechanism and Ross’s view, see Glennan (2025).
This is clarified in what follows, where we discuss the “p53 degradation mechanism” or “p53 degradation pathway".
Bechtel (2020b, p. 1) has recently challenged the idea that “network representations are flat while mechanisms are organized into a hierarchy of levels” suggesting that the lesson to be drawn from the ways in which large-scale networks are analyzed in systems biology is different. Networks can be conceived as “clusters of nodes that operate as modules or mechanisms” (p. 1), stressing connectivity patterns holding between entities, and “bio-ontologies such as gene ontology (GO) [can be used] to annotate nodes with information about where entities appear in cells and the biological functions in which they participate” (p.1). This is taken to both support a mechanistic interpretation of networks and to be heuristically fruitful, providing new mechanistic knowledge on the parts and operations of the systems at stake. Rather than being opposed, mechanistic and network approaches are often used together, with networks too being interpreted as representing hierarchies of levels. Furthermore, processes enter the picture as well and are totally compatible with it: “nodes that cluster in the network and are annotated with the same biological process can be viewed as parts of mechanisms involved in those processes” (Bechtel 2020b, p. 6). A different view is held by Philippe Huneman (2025), who contrasts network analysis with a mechanistic methodology, while arguing that network analyses can also be explanatory.
This example is taken from Boniolo and Lanfrancone (2016).
In this case, following the nomenclature indicated by the HUGO Gene Nomenclature Committee; (www.genenames.org) MITF is the Microphthalmia associated transcription factor; SRC is the sarcoma viral oncogene homolog; SHCA is the SRC homology 2 domain containing, transforming protein A; Grb2 is the growth factor receptor-bound protein 2; SOS is the Son of Sevenless; GTP is the guanosine triphosphate; ATP is the adenosine triphosphate; PI3K is the phosphatidylinositol-4,5-bisphosphate 3-kinase; AKT is the serine/threonine-specific protein kinase; PIP2 is the phosphatidylinositol bisphosphate; PIP3 is the phosphatidylinositol trisphosphate; PDK1 is the phosphoinositide-dependent kinase-1; MAPK is the mitogen-activated protein kinases, originally called ERK (Extracellular signal-regulated kinases); MEK is the mitogen-activated protein kinase kinase; RAS is the Rat Sarcoma protein; RAF is a serine/threonine-protein kinase; GSK is the glycogen synthase kinase.
Grb2 is an adaptor protein involved in the signal transduction cascade downstream of several receptors, while SOS is a guanine nucleotide exchange factor that activates RAS. Stimulating the RAS/MAPK pathway finally leads to MITF activation by its direct phosphorylation (Samayawardhena and Pallen 2008). MITF is a transcription factor whose transactivation activity is increased when phosphorylated, resulting in increased proliferation of melanocytic cells (Vance and Goding 2004; Phung et al. 2011).
References
Andersen H (2014b) A field guide to mechanisms: Part II. Philos Compass 9(4):284–293
Andersen H (2014a) A field guide to mechanisms: Part I. Philos Compass 9(4):274–283
Aoki-Kinoshita KF, Kanehisa M (2007) Gene annotation and pathway mapping in KEGG. Methods Mol Biol 396:71–91
Aristotle (2014) Rhetoric (trans: Roberts WR). Dover, New York
Aronson JK, La Caze A, Kelly MP, Parkkinen VP, Williamson J (2018) The use of mechanistic evidence in drug approval. J Eval Clin Pract 24:1–11
Aronson J (2020) Defining aspects of mechanisms: evidence-based mechanism (evidence for a mechanism), mechanism-based evidence (evidence from a mechanism), and mechanistic reasoning. In: LaCaze A, Osimani B (eds) Uncertainty in pharmacology. Epistemology, methods and decisions. Springer, Dordrecht, pp 3–38
Austin C (2020) Organisms, activity, and being: on the substance of process ontology. Eur J Philos Sci 10:13
Balorda V, Šustar P (2025) Natural selection: a mechanism, a pathway or a little bit of both? J Gen Philos Sci 56:417–433
Bechtel W (2018) The importance of constraints and control in biological mechanisms: insights from cancer research. Philos Sci 85:573–593
Bechtel W (2019) From parts to mechanisms: research heuristics for addressing heterogeneity in cancer genetics. Hist Philos Life Sci 41(3):27
Bechtel W (2020b) Hierarchy and levels: analysing networks to study mechanisms in molecular biology. Phil Trans R Soc B 375:20190320. https://doi.org/10.1098/rstb.2019.0320
Bechtel W, Abrahamsen A (2005) Explanation: a mechanist alternative. Stud History Philos Sci 36:421–441
Bechtel W (2020a) Rethinking psychiatric disorders in terms of heterarchical networks of control mechanisms. In: Kendler K, Parnas J, Zachar P (eds) Levels of analysis in psychopathology. Cambridge University Press, Cambridge, pp 24–46
Bergmann C (1957) Philosophy of science. University of Wisconsin Press, Madison
Bertolaso M, Dupré J (2018) A processual perspective on cancer. In: Dupré J, Nicholson D (eds) Everything flows. Cambridge University Press, Cambridge, pp 311–336
Bonetta L (2010) Interactome under construction. Nature 468:851–852
Boniolo G, Campaner R (2018) Molecular pathways and the contextual explanation of molecular functions. Biol Philos 33:24
Boniolo G, Campaner R (2022) The logic of explanation in molecular biology: historical-processual and logical-procedural aspects. Eur J Philos Sci 12(15). https://doi.org/10.1007/s13194-022-00445-1
Boniolo G, Lanfrancone L (2016) Decomposing biological complexity into a conjunction of theorems. The case of the melanoma network. Humana Mente J Philosophical Stud 30:19–35
Boniolo G, D’Agostino M, Di Fiore PP (2010) Zsyntax: a formal language for molecular biology with projected applications in text mining and biological prediction. PLOsONE 5(3):e9511
Boniolo G, DʼAgostino M, Piazza M, Pulcini G (2012) A logic of non-monotonic interactions. J Appl Log 11:52–62
Boniolo G, DʼAgostino M, Piazza M, Pulcini G (2015) Adding logic to the toolbox of molecular biology. Eur J Philos Sci 5:399–417
Broadbent A (2011) Inferring causation in epidemiology: Mechanisms, black boxes, and contrasts. In: Illari P, Russo F, Williamson J (eds) Causality in the sciences. Oxford University Press, Oxford, pp 45–69
Bruck J, Ebenhöh O, Heinrich R (2006) Patterns of interactions of reaction pairs in metabolic networks. Genome Inf 17:208–218
Brzović Z, Balorda V, Šustar P (2021) Explanatory Hierarchy of Causal Structures in Molecular Biology. Eur J Philos Sci 11:1–21
Campaner R (2010) Understanding mechanisms in the health sciences. Theor Med Bioeth 32:5–17
Campaner R (2016) Mechanistic models and modeling disorders. In: Ippoliti E, Nickles T, Sterpetti F (eds) Models and inferences in science. Springer, Dordrecht, pp 113–132
Campbell J (2013) Causation and mechanisms in psychiatry. In: Fulford KWM, Davies M, Gipps R, Graham G, Sadler JZ, Stanghellini G, Thornton T (eds) Oxford handbook of philosophy and psychiatry. Oxford University Press, Oxford, pp 935–949
Canali S (2019) Evaluating evidential pluralism in epidemiology: Mechanistic evidence in exposome research. Hist Philos Life Sci 41:4. https://doi.org/10.1007/s40656-019-0241-6
Cho DY, Kim Y-A, Przytycka TM (2012) Network biology approach to complex diseases. PLoS Comput Biol 8(12):e1002820
Cordovil JL, Santos G, Vecchi D (2024) New mechanism. Explanation, emergence and reduction. Springer Nature, Cham
Craver CF (2006) When mechanistic models explain. Synthese 153: 355–376
Craver FC, Darden L (2013) In search of mechanisms: discoveries across the life sciences. The University of Chicago Press, Chicago
Craver C, Tabery T, Illari P (2024) Mechanism in science. Stanford encyclopedia of philosophy https://plato.stanford.edu/entries/science-mechanisms/
Darden L, Craver C (2013) In search of mechanisms. The University of Chicago Press, Chicago
Davies MA (2012) The role of the PI3K-AKT pathway in melanoma. Cancer J 18:142–147
Duprè J, Nicholson D (eds) (2018) Everything flows. Oxford University Press, Oxford
Faeder JR, Blinov ML, Hlavacek W (2005) In: Liebrock LM (ed) Graphical rule-based representation of signal-transduction networks. ACM, New York, pp 133–140
Glennan S (2005) Modeling mechanisms. Studies in history and philosophy of science part C: studies. history Philos Biol biomedical Sci 36(2):443–464
Glennan S (2017) The new mechanical philosophy. Oxford University Press, Oxford
Glennan S (2025) On mechanisms, pathways and their models. Biology Philos 40:24
Glennan S, Illari P (eds) (2018) The Routledge handbook of mechanisms and mechanical philosophy. Routledge, New York
Gostissa M, Hofmann TG, Will H, Del Sal G (2003) Regulation of p53 functions: let’s meet at the nuclear bodies. Curr Opin Cell Biol 15:351–357
Hainaut P, Wiman KG (eds) (2005) 25 Years of p53 research. Springer, Dordrecht
Hartner R, Theurer K (2018) Psychiatry should not seek mechanisms of disorder. J Theoretical Philosophical Psychol 38:4
Hofseth LJ, Hussain SP, Harris CC (2004) p53: 25 years after its discovery. Trends Pharmacol Sci 25:177–181
Huneman P (2025) What kind of epistemology for network analyses? https://doi.org/10.1007/s11229-025-05105-4 Synthese 206:107
Illari P, Williamson J (2012) What is a mechanism? Thinking about mechanisms across the sciences. Eur J Philos Sci 2(1):119–135
Ioannidis S, Psillos S (eds) (2022) Mechanisms in science. Method or metaphysics? Cambridge University Press, Cambridge
James W (1907) Pragmatism: a new name for some old ways of thinking. Longmans, Green & Co, London
Kanehisa M (2013) Molecular network analysis of diseases and drugs in KEGG. Methods Mol Biol 939:263–275
Kanehisa M, Goto S, Kawashima S, Okuno Y, Hattori M (2004) The KEGG resource for deciphering the genome. Nucleic Acids Res 32:D277–280
Kanehisa M, Goto S, Hattori M, Aoki-Kinoshita KF, Itoh M, Kawashima S, Katayama T, Araki M, Hirakawa M (2006) From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res 34:D354–357
Kantor R (1953) The logic of modern science. Principia Press, Chicago
Kendler K (2020) A typology of levels of mechanisms involved in the etiology of psychiatric illness. In: Kendler K, Parnas J, Zachar P (eds) Levels of analysis in psychopathology. Cambridge University Press, Cambridge, pp 47–53
Kitano H, Funahashi A, Matsuoka Y, Oda K (2005) Using process diagrams for the graphical representation of biological networks. Nat Biotechnol 23:961–966
Kohn KW (1999) Molecular interaction map of the mammalian cell cycle control and DNA repair systems. Mol Biol Cell 10:2703–2734
Krickel B (2018) The mechanical world. The metaphysical commitments of the new mechanistic approach. Springer, Dordrecht
Lennartsson J, Ronnstrand L (2012) Stem cell factor receptor/c-Kit: from basic science to clinical implications. Physiol Rev 92:1619–1649
Levy A (2013) Three kinds of new mechanism. Biol Philos 28:99–114
Lima-Mendez G, van Helden J (2009) The powerful law of the power law and other myths in network biology. Mol Biosyst 5:1482–1493
Mach E (1886) Beiträge zur Analyse der Empfindungen. Gustav Fischer, Jena
Machamer P (2004) Activities and causation: The metaphysics and epistemology of mechanisms. Int Stud Philos Sci 18:27–39
Machamer P, Darden L, Craver CF (2000) Thinking about mechanisms. Philos Sci 67:1–25
Marchi S, Zanella M, Pinton P, Crafa S, Boniolo G (2021) MitopatHs: a new logically-framed tool for visualizing multiple mitochondrial pathways. Science 24:102324. https://doi.org/10.1016/j.isci.2021.102324
Masson K, Ronnstrand L (2009) Oncogenic signaling from the hematopoietic growth factor receptors c-Kit and Flt3. Cell Signal 21:1717–1726
Matthews L, Tabery J (2017) Mechanisms and the metaphysics of causation. Routledge, New York
Meincke AS (2019) Autopoiesis, biological autonomy and the process view of life. Eur J Philos Sci 9:5
Meincke AS, Dupré J (eds) (2020) Biological identity: perspectives from metaphysics and the philosophy of biology. Routledge, London
Moss L (2012) Is the philosophy of mechanism philosophy enough? Studies in History and Philosophy of Science Part C: Studies in History and Philosophy of. Biol Biomedical Sci 43:1:164–172
Phung B, Sun J, Schepsky A, Steingrimsson E, Rönnstrand L (2011) C-KIT signaling depends on microphthalmia-associated transcription factor for effects on cell proliferation. PloSOne 6:e24064. https://doi.org/10.1371/journal.pone.0024064
Plewczyński D, Ginalski K (2009) The interactome: predicting the protein-protein interactions in cells. Cell Mol Biol Lett 14(1):1–22
Qi Y, Ge H (2006) Modularity and dynamics of cellular networks. PLoS Comput Biol 2:e174
Reese HW (1999) Explanation is not description. Behavioral Development, 8(1): 3–7
Ronnstrand L (2004) Signal transduction via the stem cell factor receptor/c-Kit. Cellular and molecular life sciences. CMLS 61:2535–2548
Roskoski RJr (2005) Signaling by Kit protein-tyrosine kinase–the stem cell factor receptor. Biochem Biophys Res Commun 337:1–13
Ross LN (2021) Causal concepts in biology: How pathways differ from mechanisms and why it matters. Br J Philos Sci 72(1):131–158
Salmon W (1984) Scientific explanation and the causal structure of the world. Pittsburgh University, Pittsburgh
Salmon W (1998) Causality and explanation. Oxford University Press, Oxford-New York
Salmon W (1989) Four decades of scientific explanation. In: Kitcher P, Salmon W (eds) Scientific explanation. Minnesota Studies in the Philosophy of Science XII. Minnesota University, Minneapolis, pp 3–219
Samayawardhena LA, Pallen CJ (2008) Protein-tyrosine phosphatase alpha regulates stem cell factor-dependent c-Kit activation and migration of mast cells. J Biol Chem 283:29175–29185
Schaffner FK (2016) Behaving: What’s genetic, what’s not, and why should we care? Oxford University Press, Oxford
Sinha AU, Kaimal V, Chen J, Jegga AG (2008) Dissecting microregulation of a master regulatory network. BMC Genomics 9:88
Skinner B F (1931) The concept of the reflex in the description of behavior. Journal of General Psychology, 5, 427–457
Terragni J, Nayak G, Banerjee S, Medrano JL, Graham JR, Brennan JF, Sepulveda S, Cooper GM (2011) The E-box binding factors Max/Mnt, MITF, and USF1 act coordinately with FoxO to regulate expression of proapoptotic and cell cycle control genes by phosphatidylinositol 3-kinase/Akt/glycogen synthase kinase 3 signaling. J Biol Chem 286:36215–36227
Thagard P (2003) Pathways to biomedical discovery. Philos Sci 70:235–254
Toulmin S (1953) The philosophy of science: an introduction. Hutchinson's University Library, London
Vance KW, Goding CR (2004) The transcription network regulating melanocyte development and melanoma. Pigment Cell Res 17:318–325
Vidal M, Cusick ME, Barabási AL (2011) Interactome networks and human disease. Cell 144:986–998
Vogelstein B, Lane D, Levine A (2000) Surfing the p53 network. Nature 408:307–310
Wellbrock C, Rana S, Paterson H, Pickersgill H, Brummelkamp T, Marais R (2008) Oncogenic BRAF regulates melanoma proliferation through the lineage specific factor MITF. PLoS ONE 3:e2734
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Boniolo, G., Campaner, R. Mechanisms, Pathways, and Networks: On Their Description and Explanation. Biol Theory (2026). https://doi.org/10.1007/s13752-026-00550-x
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DOI: https://doi.org/10.1007/s13752-026-00550-x