The editors regret that an incorrect version of the Introduction was published and would like to apologise for any inconvenience caused. Introduction to the HUPO 2015 Special Issue The 14th Annual World Congress of the Human Proteome Organization (HUPO 2015) was held in Vancouver, BC, Canada on September 27-30, 2015. This very successful meeting attracted nearly 1200 attendees from 47 countries, and involved a total of over 700 presentations. Twelve of these presentations are featured in this special HUPO 2015 edition of the Journal of Proteomics. Like the meeting itself, these papers cover a broad range of topics involving the study of the Human Proteome, including protein digestion methods to help find “missing” proteins, biomarker discovery studies, new crosslinkers for structural proteomics, a new method for aligning MALDI images, and a comparison of in vitro model systems for the metabolism of doping compounds. The first paper in this special issue, by Ruelcke, et al. , discusses a new method for low-cost automation of geLC-MS (the combination of in-gel digestion with either direct MALDI or LC/ESI-MS/MS analysis for identification of the proteins). This method uses standard 96 well plates and provides results comparable to manual tryptic digestion. The authors have also included a method file for use on the Agilent Bravo liquid handling robot. Regarding tryptic digestion, two other papers focus on improving the detection of “missing” proteins. The first paper, from the Yamamoto group , is a biostatistical comparison of proteins that are or are not detected. The authors confirmed the relationship between the presence of transmembrane domains (TMDs) and difficulty in detection of the protein. The next paper on this topic, by Vit, et al., , focuses on the experimental detection of these TMD-containing proteins, and presents a new digestion protocol that improves the detection of TMD-containing proteins. Both papers, therefore, are important for the chromosome-centric Human Proteome Project, where evidence is being sought for all of the proteins encoded by each human chromosome. As is to be expected for a HUPO conference, many papers described the detection of biomarkers for different diseases. Choi, et al.  used the Luminex platform to determine serum levels of 10 potential cytokine and peptide biomarkers for pulmonary tuberculosis. Reflecting the current search for biomarkers in a less complex biofluid than serum or plasma, and which requires less-invasive sample collection, several papers identified potential urinary biomarkers of various diseases. These include a paper from the Nikolaev laboratory  on the identification of biomarkers for infectious and non-infectious lung disease in preterm newborns, a particularly appropriate group of patients for non-invasive sampling techniques. In another project using non-targeted LC/MS/MS, the Nikolaev group examined urine samples from pregnant women and found peptides which were able to distinguish normal patients from those with mild or severe preclampsia . Vuong, et al. , examined the effects of exposure to carbon black and titanium dioxide particles on the proteome of human lung epithelial cell lines, using cytotoxicity assays combined with 2D gel electrophoresis followed by MALDI-TOF MS protein identification. Wölter, et al.  used affinity purification of a class of proteins, and developed a MALDI-based assay for the relative quantitation of different proteoforms of Intrauterine Growth Restriction (IUGR) in the serum of pregnant women. IUGR is a key factor in perinatal fetal morbidity and mortality, requiring medically-induced preterm birth to prevent fetal death. Affinity purification can not only be used for simplifying the mixture to be analyzed – it can also be used to determine the members of different protein complexes. In a paper on the ProHits software package, the Gingras laboratory describes the implementation of Significance Analysis of INTeractomes (SAINT) which scores the observed potential interactions on the basis of spectral counts . Crosslinking can be used in conjunction with purified protein complexes to turn transient interactions into permanent covalent interactions. Typical amino-reactive crosslinkers provide long spacer lengths (~ 14 Å in length) and can provide information on the members of a complex and the connected peptides, but for molecular modeling, short-range crosslinkers are needed to provide tight constraints for determining the 3D structure and the folding pattern of a protein. In a paper from the Borchers laboratory, a new crosslinker, 2,4,6-triazido triazine (TATA), is described for the generation of crosslinks of approximately 5 Å in length . This issue also includes a paper by the Caprioli group on imaging mass spectrometry. The mass spectrometry imaging (MSI; also known as MALDI Imaging) technique was pioneered by Richard Caprioli approximately 20 years ago, and provides spatial information about the location of a protein or metabolite within a tissue. This new study is on the 3-dimensional (3D) imaging of mouse optic nerves to determine differences between tumor-bearing nerves and normal tissue , and relates to a common neurogenetic disorder (neurofibromatosis type 1) in children which can lead to brain tumors (gliomas) and impaired vision. In this paper, a new method for aligning multimodal images which simplifies 3D image reconstruction is presented. Also in this issue is a paper by Zvereva, et al  on the use of several in vitro model systems (human serum, and human kidney microsomes, and the liver S9 fraction) to study the metabolism of small synthetic (< 2KD) doping peptides. As can be seen from the articles in this special issue, HUPO conferences cover a wide range of exciting topics, including methods papers, applications, and bioinformatics studies. We invite you to participate in the 16th Annual World Congress of the Human Proteome Organization (HUPO 2017), to be held in Dublin, Ireland on September 17-20, 2017 (http://hupo2017.ie/). References  J.E. Ruelcke, D. Loo, M.M. Hill, Reducing the Cost of Semi-Automated In-Gel Tryptic Digestion and GeLC Sample Preparation for High-Throughput Proteomics, J. Proteomics 149 (2016) 3–6.  A. Elguoshy, S. Magdeldin, B. Xu, Y. Hirao, et al., Why they are missing?: Bioinformatics characterization of missing human proteins, J. Proteomics 149 (2016) 7–14.  O. Vit, P. Man, A. Kadek, J. Hausner, et al., Large-scale identification of membrane proteins based on analysis of trypsin-protected transmembrane segments, J. Proteomics 149 (2016) 15–22.  R. Choi, K. Kim, M.-J. Kim, S.-Y. Kim, et al., Serum inflammatory profiles in pulmonary tuberculosis and their association with treatment response, J. Proteomics 149 (2016) 23–30.  N.L. Starodubtseva, A.S. Kononikhin, A.E. Bugrova, V. Chagovets, et al., Investigation of Urine Proteome of Preterm Newborns With Respiratory Pathologies, J. Proteomics 149 (2016) 31–37.  A.S. Kononikhin, N.L. Starodubtseva, A.E. Bugrova, V.A. Shirokova, et al., An Untargeted Approach for the Analysis of the Urine Peptidome of Women with Preeclampsia, J. Proteomics 149 (2016) 38–43.  N.Q. Vuong, P. Goegan, S. Mohottalage, D. Breznan, et al., Proteomic changes in human lung epithelial cells (A549) in response to carbon black and titaniumdioxide exposures, J. Proteomics 149 (2016) 53–63.  M.Wölter, C. Röwer, C. Koy,W. Rath, et al., Proteoform Profiling of Peripheral Blood Serum Proteins from PregnantWomen Provides a Molecular IUGR Signature, J. Proteomics 149 (2016) 44–52.  G. Liu, J.D. Knight, J.P. Zhang, C.-C. Tsou, et al., Data Independent Acquisition analysis in ProHits 4.0, J. Proteomics 149 (2016) 64–68.  N.I. Brodie, E.V. Petrotchenko, C.H. Borchers, The novel isotopically coded shortrange photo-reactive crosslinker 2,4,6-triazido-1,3,5-triazine (TATA) for studying protein structures, J. Proteomics 149 (2016) 69–76.  D.M.G. Anderson, R. Van de Plas, K.L. Rose, S. Hill, et al., 3-D ImagingMass Spectrometry of Protein Distributions in Mouse Neurofibromatosis (NF1)-Associated Optic Glioma, J. Proteomics 149 (2016) 77–84.  I. Zvereva, E. Semenistaya, G. Krotov, G. Rodchenkov, Comparison of various in vitro model systems of the metabolism of synthetic doping peptides: proteolytic enzymes, human blood serum, liver and kidney microsomes and liver S9 fraction, J. Proteomics 149 (2016) 85–97.