Technology Made Legible: A Cultural Study of Software as a Form of Writing in the Theories and Practices of Software Engineering

My dissertation proposes an analytical framework for the cultural understanding of the group of technologies commonly referred to as 'new' or 'digital'. I aim at dispelling what the philosopher Bernard Stiegler calls the 'deep opacity' that still surrounds new technologies, and that constitutes one of the main obstacles in their conceptualization today. I argue that such a critical intervention is essential if we are to take new technologies seriously, and if we are to engage with them on both the cultural and the political level. I understand new technologies as technologies based on software. I therefore suggest that a complex understanding of technologies, and of their role in contemporary culture and society, requires, as a preliminary step, an investigation of how software works. This involves going beyond studying the intertwined processes of its production, reception and consumption - processes that typically constitute the focus of media and cultural studies. Instead, I propose a way of accessing the ever present but allegedly invisible codes and languages that constitute software. I thus reformulate the problem of understanding software-based technologies as a problem of making software legible. I build my analysis on the concept of software advanced by Software Engineering, a technical discipline born in the late 1960s that defines software development as an advanced writing technique and software as a text. This conception of software enables me to analyse it through a number of reading strategies. I draw on the philosophical framework of deconstruction as formulated by Jacques Derrida in order to identify the conceptual structures underlying software and hence 'demystify' the opacity of new technologies. Ultimately, I argue that a deconstructive reading of software enables us to recognize the constitutive, if unacknowledged, role of technology in the formation of both the human and academic knowledge. This reading leads to a self-reflexive interrogation of the media and cultural studies' approach to technology and enhances our capacity to engage with new technologies without separating our cultural understanding from our political practices

AI that Matters:A Feminist Approach to the Study of Intelligent Machines

n this chapter, Drage and Frabetti argue that computer code uses data to not only make statements about the world but also bring that world into existence. Drawing on the concept of performativity, arguably gender studies’ best-known export, they explain why we must view artificial intelligence (AI) as performative to understand how it genders and racialises populations even when it appears to be ‘unbiased’ or correctly functioning. In its reading of neural networks, ‘AI that Matters: A Feminist Approach to the Study of Intelligent Machines’ demonstrates that Facial Detection and Recognition Technologies and Automatic Gender Recognition never objectively identify or recognise a person (or their gender), as they claim to do. Instead, drawing on work by Judith Butler and Karen Barad, they merely comment on and annotate a person’s body in accordance with dominant social rules and perspectives. They present this framing as an intervention into misguided attempts to treat discrimination as an error that can be corrected by a better functioning machine

Systematic analysis of mRNA 5' coding sequence incompleteness in Danio rerio: an automated EST-based approach

<p>Abstract</p> <p>Background</p> <p>All standard methods for cDNA cloning are affected by a potential inability to effectively clone the 5' region of mRNA. The aim of this work was to estimate mRNA open reading frame (ORF) 5' region sequence completeness in the model organism <it>Danio rerio </it>(zebrafish).</p> <p>Results</p> <p>We implemented a novel automated approach (<it>5'_ORF_Extender</it>) that systematically compares available expressed sequence tags (ESTs) with all the zebrafish experimentally determined mRNA sequences, identifies additional sequence stretches at 5' region and scans for the presence of all conditions needed to define a new, extended putative ORF. Our software was able to identify 285 (3.3%) mRNAs with putatively incomplete ORFs at 5' region and, in three example cases selected (<it>selt1a</it>, <it>unc119.2</it>, <it>nppa</it>), the extended coding region at 5' end was cloned by reverse transcription-polymerase chain reaction (RT-PCR).</p> <p>Conclusion</p> <p>The implemented method, which could also be useful for the analysis of other genomes, allowed us to describe the relevance of the "5' end mRNA artifact" problem for genomic annotation and functional genomic experiment design in zebrafish.</p> <p>Open peer review</p> <p>This article was reviewed by Alexey V. Kochetov (nominated by Mikhail Gelfand), Shamil Sunyaev, and Gáspár Jékely. For the full reviews, please go to the Reviewers' Comments section.</p

Uncertainty principle of genetic information in a living cell

BACKGROUND: Formal description of a cell's genetic information should provide the number of DNA molecules in that cell and their complete nucleotide sequences. We pose the formal problem: can the genome sequence forming the genotype of a given living cell be known with absolute certainty so that the cell's behaviour (phenotype) can be correlated to that genetic information? To answer this question, we propose a series of thought experiments. RESULTS: We show that the genome sequence of any actual living cell cannot physically be known with absolute certainty, independently of the method used. There is an associated uncertainty, in terms of base pairs, equal to or greater than μs (where μ is the mutation rate of the cell type and s is the cell's genome size). CONCLUSION: This finding establishes an "uncertainty principle" in genetics for the first time, and its analogy with the Heisenberg uncertainty principle in physics is discussed. The genetic information that makes living cells work is thus better represented by a probabilistic model rather than as a completely defined object

Sequence, "subtle" alternative splicing and expression of the CYYR1 (cysteine/tyrosine-rich 1) mRNA in human neuroendocrine tumors

BACKGROUND: CYYR1 is a recently identified gene located on human chromosome 21 whose product has no similarity to any known protein and is of unknown function. Analysis of expressed sequence tags (ESTs) have revealed high human CYYR1 expression in cells belonging to the diffuse neuroendocrine system (DNES). These cells may be the origin of neuroendocrine (NE) tumors. The aim of this study was to conduct an initial analysis of sequence, splicing and expression of the CYYR1 mRNA in human NE tumors. METHODS: The CYYR1 mRNA coding sequence (CDS) was studied in 32 NE tumors by RT-PCR and sequence analysis. A subtle alternative splicing was identified generating two isoforms of CYYR1 mRNA differing in terms of the absence (CAG(- )isoform, the first described mRNA for CYYR1 locus) or the presence (CAG(+ )isoform) of a CAG codon. When present, this specific codon determines the presence of an alanine residue, at the exon 3/exon 4 junction of the CYYR1 mRNA. The two mRNA isoform amounts were determined by quantitative relative RT-PCR in 29 NE tumors, 2 non-neuroendocrine tumors and 10 normal tissues. A bioinformatic analysis was performed to search for the existence of the two CYYR1 isoforms in other species. RESULTS: The CYYR1 CDS did not show differences compared to the reference sequence in any of the samples, with the exception of an NE tumor arising in the neck region. Sequence analysis of this tumor identified a change in the CDS 333 position (T instead of C), leading to the amino acid mutation P111S. NE tumor samples showed no significant difference in either CYYR1 CAG(- )or CAG(+ )isoform expression compared to control tissues. CYYR1 CAG(- )isoform was significantly more expressed than CAG(+ )isoform in NE tumors as well as in control samples investigated. Bioinformatic analysis revealed that only the genomic sequence of Pan troglodytes CYYR1 is consistent with the possible existence of the two described mRNA isoforms. CONCLUSION: A new "subtle" splicing isoform (CAG(+)) of CYYR1 mRNA, the sequence and the expression of this gene were defined in a large series of NE tumors

Differential expression of alternatively spliced mRNA forms of the insulin-like growth factor 1 receptor in human neuroendocrine tumors

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TRAM (Transcriptome Mapper): database-driven creation and analysis of transcriptome maps from multiple sources

<p>Abstract</p> <p>Background</p> <p>Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input.</p> <p>Results</p> <p>TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified.</p> <p>Conclusions</p> <p>TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at <url>http://apollo11.isto.unibo.it/software/</url>, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.</p

Complexity of Bidirectional Transcription and Alternative Splicing at Human RCAN3 Locus

Human RCAN3 (regulator of calcineurin 3) belongs to the human RCAN gene family