Bioinformatics

- Continuous signals in time and amplitudes, discrete time symbolic sequences; the case of the genome and proteins - Operations on signals, sinusoids and complex numbers - Space of signals. Energy and power of signals and sequences. - Frequency representation of signals: series and Fourier transform, DTFT, DFT, zeta transform, relation between all of those. Bandwidth of a signal - Sampling theorem. A/D and D/A conversion. - Filtering of a signal, convolution, spectral product - Indicator sequences and their transform, identification of exons on a frequency basis, mention of other techniques. - Two-dimensional Fourier transforms as the basis for image processing in the spatial frequency domain, and three-dimensional Fourier transforms applied to X-ray crystallography, used to discover the shape with which proteins are folded - Random signals. Autocorrelation of a signal and of a process, Wiener's theorem. Interpretation as a dot product. Evaluation of the SNR arising from quantization noise Long-distance correlation of genomic sequences, 1/f spectral density. Serial coding of protein sequences, its transform, consensus spectrum and characteristic frequency for homofunctional protein groups. - FTIR spectrometry based on an interferometer, which from a SP point of view is a comb filter. By moving the interferometer mirror and autocorrelation function is measured, and by the Wiener theorem its anti-transform gives the power density at the output the sample material under examination, giving cues about its chemical constituents- Information by symbol and source entropy, without and with memory. The genetic code. - Entropy of a Gaussian process, information measures for a pair of random variables: joint entropy, conditional entropies, average mutual information I(X;Y). Channel equivocation and noise entropy, channel capacity. - Information theory concepts in biochemical signaling systems, estimation of mutual information I(X;Y) in between transcription factors and gene expression. Measure of the capacity of biological "channels", data processing inequality, bias, and rate-distortion theory - Types of analog and digital filters. Numerical filtering via DFT for batch processing: discrete and circular convolution, convolution between finished duration sequences, convolution between an infinite input sequence and an impulse response with finite length. Method of Overlap and Add. FIR and IIR digital computational architectures used for real time processing

Calculus and mathematical analysis, derivatives and integrals, multivariate functions, linear and matrix algebra. Probability and statistics.

First of all, keep in mind that the official website of the course is hosted at an address external to Sapienza, managed directly by the teacher in the context of his Free Culture project https://teoriadeisegnali.it/wiki/Didattica/SignalProcessingAndInformationTheory. The Google Classroom site is instead used mainly as a tool for communicating with students during the course of the year. In any case, in January 2024 I updated both this site and all the others :-) During the previous years in which the course was taught, I created a series of slides to be projected in the classroom, which in my opinion represent a good compromise between expository synthesis and clarity of content, and which are available individually as indicated on https://teoriadeisegnali.it/to-slide-or-not-to-slide/, or all together in zipped format at this other address https://teoriadeisegnali.it/story/pub/bioinf/slide.zip. Furthermore, the part about X-ray crystallography and 3D signal processing can be found here https://teoriadeisegnali.it/items/le-armoniche-di-un-cristallo/ I have been working on a book on signals and telecommunications for over twenty years, and this course is giving me the opportunity to translate it. I will be very grateful if you would point out any corrections to me! You can download it's actual shape at https://teoriadeisegnali.it/items/signal-processing-and-information-theory/. Italian speakers may prefer to read the Italian version of the book, which can be accessed at https://teoriadeisegnali.it/sfoglia-il-testo-trasmissione-dei-segnali-e-sistemi-di-telecomunicazione/ Other material is still being identified. Below what I have preliminarily found, I will give indications on what to read during the course See the list below, which may be subject to variations. Lastly, an abridged version of one of my online texts, translated for the occasion, and distributed to students is indicated. During the lesson, in addition to the classic blackboard, specially prepared slides are used, as well as other audiovisual material, as well as software and web browsing experiments. All the material produced is available on the page relating to the lessons of past years, that is here https://teoriadeisegnali.it/wiki/Didattica/SPaIT-aa2324

Il corso si svolge in maniera tradizionale, in aula. In funzione di possibili esigenze sanitarie, potrà essere svolto anche in modalità mista, o solamente a distanza.

Attendance is optional, but attendance is recommended

The student is asked to answer written questions regarding the contents illustrated in class. Some questions require a descriptive answer, while others require reasoning, and possibly simple calculations carried out, and / or expressed the result in graphical form. Unanswered questions may be given additional time to complete the test at home.

Genomic Signal Processing D. Anastassiou, Genomic Signal Processing (2001) - http://www.ece.iit.edu/~biitcomm/research/references/Other/Genomic%20Signal%20Processing/GSP.pdf P. Ramachandran, A. Antoniou, Genomic Digital Signal Processing (slides) - https://www.ece.uvic.ca/~andreas/RLectures/GenomicDSP04-Paramesh-Pres.pdf P.P. Vaidyanathan, Genomics and Proteomics: A Signal Processor’s Tour (2004) http://gladstone.systems.caltech.edu/dsp/ppv/papers/CASGeneGalley.pdf R. Palaniappan, Biological Signal Analysis, https://bookboon.com/en/introduction-to-biological-signal-analysis-ebook J.V. Lorenzo-Ginori et al, Digital Signal Processing in the Analysis of Genomic Sequences (2009) - https://www.researchgate.net/profile/Juan-Lorenzo-Ginori/publication/228359227_Digital_Signal_Processing_in_the_Analysis_of_Genomic_Sequences/links/0fcfd5111298c0ae8d000000/Digital-Signal-Processing-in-the-Analysis-of-Genomic-Sequences.pdf Insights into some topics G. Alterovitz, M.F. Ramoni Ed., Systems Bioinformatics - An Engineering Case-Based Approach (2007) - https://www.codecool.ir/extra/202033231410343Systems%20Bioinformatics_%20An%20Engineering%20Case-Based%20Approach.pdf Edward R Dougherty et al, Genomic Signal Processing and Statistics (2005) - https://downloads.hindawi.com/books/9789775945075.pdf More advanced topics Steven W. Smith, The Scientist and Engineer's Guide to Digital Signal Processing, (2011) - http://www.dspguide.com/ W. Zhang et al, Network-based machine learning and graph theory algorithms for precision oncology (2017) - https://www.nature.com/articles/s41698-017-0029-7 A. Ortega et al, Graph Signal Processing: Overview, Challenges and Applications (2018) - https://arxiv.org/abs/1712.00468 Y. Li et al, Deep learning in bioinformatics: introduction, application, and perspective in big data era (2019) - https://arxiv.org/abs/1903.00342 X.M. Zhang et al, Graph Neural Networks and Their Current Applications in Bioinformatics (2021) - https://www.frontiersin.org/articles/10.3389/fgene.2021.690049/full All the drive of downloaded articles https://drive.google.com/drive/folders/1jjO5kla_zCjZ8G_F8Q-Vxe6ptPdU8itc?usp=sharing

Il corso si svolge in maniera tradizionale, in aula. In funzione di possibili esigenze sanitarie, potrà essere svolto anche in modalità mista, o solamente a distanza.