Below are about a dozen or so examples of areas where ID is helping science to generate new knowledge. Each example includes citations to mainstream scientific articles and publications by ID proponents that discuss this research:

ID has inspired scientists to do research which has detected high levels of complex and specified information in biology in the form of fine-tuning of protein sequences. This has practical implications not just for explaining biological origins but also for engineering enzymes and anticipating / fighting the future evolution of diseases. (See Douglas D. Axe, "Extreme Functional Sensitivity to Conservative Amino Acid Changes on Enzyme Exteriors," Journal of Molecular Biology, Vol. 301:585-595 (2000); Douglas D. Axe, "Estimating the Prevalence of Protein Sequences Adopting Functional Enzyme Folds," Journal of Molecular Biology, Vol. 341:1295-1315 (2004); Douglas D. Axe, "The Case Against a Darwinian Origin of Protein Folds," Bio-Complexity, Vol. 2010).)

ID has inspired scientists to seek and find instances of fine-tuning of the laws and constants of physics to allow for life, leading to a variety of fine-tuning arguments including the Galactic Habitable Zone. This has huge implications for proper cosmological models of the universe, hints at proper avenues for successful "theories of everything" which must accommodate fine-tuning, and other implications for theoretical physics. (See Guillermo Gonzalez et al., "Refuges for Life in a Hostile Universe," Scientific American (October, 2001); D. Halsmer, J. Asper, N. Roman, T. Todd, "The Coherence of an Engineered World," International Journal of Design & Nature and Ecodynamics, Vol. 4(1):47-65 (2009).)

ID has inspired scientists to understand intelligence as a scientifically studyable cause of biological complexity, and to understand the types of information it generates. (See Stephen C. Meyer, "The origin of biological information and the higher taxonomic categories," Proceedings of the Biological Society of Washington, Vol. 117(2):213-239 (2004); W.A. Dembski, The Design Inference: Eliminating Chance through Small Probabilities (Cambridge: Cambridge University Press, 1998); A.C. McIntosh, "Information and Entropy -- Top-Down or Bottom-Up Development in Living Systems?," International Journal of Design & Nature and Ecodynamics, Vol. 4(4):351-385 (2009).)

ID has inspired both experimental and theoretical research into how limitations on the ability of Darwinian evolution to evolve traits that require multiple mutations to function. This of course has practical implications for fighting problems like antibiotic resistance or engineering bacteria. (See Michael Behe & David W. Snoke, "Simulating evolution by gene duplication of protein features that require multiple amino acid residues," Protein Science, Vol. 13 (2004); Ann K Gauger, Stephanie Ebnet, Pamela F Fahey, Ralph Seelke, "Reductive Evolution Can Prevent Populations from Taking Simple Adaptive Paths to High Fitness," Bio-Complexity, Vol. 2010).

ID has inspired theoretical research into the information-generative powers of Darwinian searches, leading to the finding that the search abilities of Darwinian processes are limited, which has practical implications for the viability of using genetic algorithms to solve problems. (See: William A. Dembski and Robert J. Marks II, "Conservation of Information in Search: Measuring the Cost of Success," IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and Humans, Vol. 39(5):1051-1061 (September, 2009); Winston Ewert, William A. Dembski, and Robert J. Marks II, "Evolutionary Synthesis of Nand Logic: Dissecting a Digital Organism," Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics, (October, 2009); William A. Dembski and Robert J. Marks II, "Bernoulli's Principle of Insufficient Reason and Conservation of Information in Computer Search," Proceedings of the 2009 IEEE International Conference on Systems, Man, and Cybernetics, (October, 2009); Winston Ewert, George Montanez, William Dembski and Robert J. Marks II, "Efficient Per Query Information Extraction from a Hamming Oracle," 42nd South Eastern Symposium on System Theory, 290-297(March, 2010); Douglas D. Axe, Brendan W. Dixon, Philip Lu, "Stylus: A System for Evolutionary Experimentation Based on a Protein/Proteome Model with Non-Arbitrary Functional Constraints," PLoS One, Vol. 3(6):e2246 (June 2008).)

ID has inspired scientists to study proper measures of biological information, leading to concepts like complex and specified information or functional sequence complexity. This allows us to better quantify complexity and understand what features are, or are not, within the reach of Darwinian evolution. (See, for example, Stephen C. Meyer, "The origin of biological information and the higher taxonomic categories," Proceedings of the Biological Society of Washington, Vol. 117(2):213-239 (2004); Kirk K. Durston, David K. Y. Chiu, David begin_of_the_skype_highlighting     end_of_the_skype_highlighting L. Abel, Jack T. Trevors, "Measuring the functional sequence complexity of proteins," Theoretical Biology and Medical Modelling, Vol. 4:47 (2007); Chiu, David K.Y., and Lui, Thomas W.H., "Integrated Use of Multiple Interdependent Patterns for Biomolecular Sequence Analysis," International Journal of Fuzzy Systems, Vol 4(3):766-775 (September, 2002).)

ID has inspired scientists to investigate computer-like properties of DNA and the genome in the hopes of better understanding genetics and the origin of biological systems. (See Richard v. Sternberg, "DNA Codes and Information: Formal Structures and Relational Causes," Acta Biotheoretica, Vol. 56(3):205-232 (September, 2008); Ø. A. Voie, "Biological function and the genetic code are interdependent," Chaos, Solitons and Fractals, Vol 28(4) (2006): 1000-1004; David L. Abel & Jack T. Trevors, "Self-organization vs. self-ordering events in life-origin models," Physics of Life Reviews, Vol. 3:211-228 (2006).)

ID has inspired scientists to reverse engineer molecular machines like the bacterial flagellum to understand their function like machines, and to understand how the machine-like properties of life allow biological systems to function. (See for example Minnich, Scott A., and Stephen C. Meyer. "Genetic Analysis of Coordinate Flagellar and Type III Regulatory Circuits in Pathogenic Bacteria," Proceedings of the Second International Conference on Design & Nature, Rhodes Greece, edited by M.W. Collins and C.A. Brebbia (WIT Press, 2004); A.C. McIntosh, "Information and Entropy -- Top-Down or Bottom-Up Development in Living Systems?," International Journal of Design & Nature and Ecodynamics, Vol. 4(4):351-385 (2009).)

ID has inspired scientists to view cellular components as "designed structures rather than accidental by-products of neo-Darwinian evolution," allowing scientists to propose testable hypotheses about causes of cancer. (See Jonathan Wells, "Do Centrioles Generate a Polar Ejection Force?." Rivista di Biologia / Biology Forum, Vol. 98:71-96 (2005).)

ID has inspired scientists to see life as being front-loaded with information such that it is designed to evolve, expecting (and now finding!) previously unanticipated "out of place" genes in various taxa. (See, for example, Michael Sherman, "Universal Genome in the Origin of Metazoa: Thoughts About Evolution," Cell Cycle, Vol. 6(15):1873-1877 (August 1, 2007); Albert D. G. de Roos, "Origins of introns based on the definition of exon modules and their conserved interfaces," Bioinformatics, Vol. 21(1):2-9 (2005); Albert D. G. de Roos, "Conserved intron positions in ancient protein modules," Biology Direct, Vol. 2:7 (2007); Albert D. G. de Roos, "The Origin of the Eukaryotic Cell Based on Conservation of Existing Interfaces," Artificial Life, Vol. 12:513-523 (2006).)

ID helps scientists explain the cause of the widespread feature of "convergent evolution," including convergent genetic evolution. (See Wolf-Ekkehard Lönnig, "Dynamic genomes, morphological stasis, and the origin of irreducible complexity," in Valerio Parisi, Valeria De Fonzo, and Filippo Aluffi-Pentini eds., Dynamical Genetics (2004); Nelson, P. & J. Wells, "Homology in biology: Problem for naturalistic science and prospect for intelligent design," in Darwinism Design and Public Education, Pp. 303-322 (Michigan State University Press, 2003); John A. Davison, "A Prescribed Evolutionary Hypothesis," Rivista di Biologia/Biology Forum 98 (2005): 155-166.)

ID helps scientists understand causes of explosions of biodiversity (as well as mass extinction) in the history of life. (See Wolf-Ekkehard Lönnig, "Dynamic genomes, morphological stasis, and the origin of irreducible complexity," in Valerio Parisi, Valeria De Fonzo, and Filippo Aluffi-Pentini eds., Dynamical Genetics (2004); Stephen C. Meyer, "The origin of biological information and the higher taxonomic categories," Proceedings of the Biological Society of Washington, Vol. 117(2):213-239 (2004); Meyer, S. C., Ross, M., Nelson, P. & P. Chien, "The Cambrian explosion: biology's big bang," in Darwinism Design and Public Education, Pp. 323-402 (Michigan State University Press, 2003).)

ID has inspired scientists to do various types of research seeking function for non-coding "junk"-DNA, allowing us to understand development and cellular biology. (See Jonathan Wells, "Using Intelligent Design Theory to Guide Scientific Research," Progress in Complexity, Information, and Design, 3.1.2 (Nov. 2004); A.C. McIntosh, "Information and Entropy -- Top-Down or Bottom-Up Development in Living Systems?," International Journal of Design & Nature and Ecodynamics, Vol. 4(4):351-385 (2009); Josiah D. Seaman and John C. Sanford, "Skittle: A 2-Dimensional Genome Visualization Tool," BMC Informatics, Vol. 10:451 (2009).)